CHARACTERISTICS AND EXPENDITURE PATTERNS OF AUSTRALIAN HOUSEHOLDS USING MOBILE PHONES. Farhat Yusuf and Mohammad B. Naseri Macquarie University

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1 CHARACTERISTICS AND EXPENDITURE PATTERNS OF AUSTRALIAN HOUSEHOLDS USING MOBILE PHONES Farhat Yusuf and Mohammad B. Naseri Macquarie University Track: Entrepreneurship, Innovation, and large and Small Business Marketing Abstract This study examines the socio-economic and demographic characteristics of Australian households which had mobile phones, and their expenditure on mobile phone services. The study is based on data collected in the Household Expenditure Survey conducted by the ABS in in a nationally representative sample of households. Our findings indicate that in there were 2.66 million households who had one or more mobile phones, which accounted for 37 % of all households. Younger and more affluent households had a higher propensity to have mobile phones, as were the migrant households from Asian and non-european countries. An average household was estimated to have spent $56.25 per month on mobile phones, which indicates that the total size of the domestic mobile phone market in was about $1.8 billion. This was the amount spent by Australian households in and did not include the cost of mobile phones used by the public and commercial sectors. Introduction Modern innovative technologies, such as the mobile phone, are becoming increasingly popular in Australia. According to the official figures there were 6.3 million subscribers in which increased to 11.1 million in 2001 (Australian Communications Authority 2001). Information about the demographics of mobile phone users and how much money they spend on this product has not been readily available, perhaps because of the commercial in-confidence nature of such data. The only source of such information at the household, but not the individual, level is the Household Expenditure Survey (HES) conducted by the Australian Bureau of Statistics in This paper presents the demographic, social and economic characteristics of the households which had one or more mobile phones, and also the estimates of the average monthly expenditure per household on mobile phone services. Literature review There have been two main streams of research in the area of diffusion of innovations. A considerable number of researchers have focused on the concept of innate innovativeness (Hirschman 1980; Midgley & Dowling 1978). They have tried to explain the adoption of a new product by consumers personality traits. However, there is no consensus among researchers as to the real meaning of innovativeness (Im, Bayus & Mason 2003). The results of empirical studies often show a poor association Entrepreneurship, Innovation and Large and Small Business Marketing Track 897

2 between innate-innovativeness and actualized innovativeness (Roehrich 2002). On the other hand, some researchers have found that domain-specific innovativeness is strongly correlated with adoption behaviour (Goldsmith, d Hauteville & Flynn 1998). The second important stream of studies, including this study, focuses on the consumers socio-demographic characteristics. At the theoretical level, there have been some attempts to explain the interrelationship between innovativeness, consumers characteristics and new product adoption behaviour (Midgley & Dowling 1978). This model has been recently tested in United States using ten consumer electronic products which included cellular car phones (Im, Bayus & Mason 2003). They found that socio-demographic variables particularly income and age were better predictors of adoption behaviour than innate-innovativeness. Findings from previous studies showed that innovators were younger, had higher education and income levels (Martinez, Polo & Flavian 1998). Some other studies have indicated weak relationships between demographics and consumers behaviour. For example, it was found that education had only indirect influence on the frequency of using ATMs and, surprisingly, higher income earners saw them less useful than low income earners (Peparmans, Verleye & Cappellen 1996). They argue that explanations which depend on demographic variables represent only a part of the reality. Also, Goldsmith and Flynn (1992) found weak relationships between demographics and innovativeness and maintain that the earlier adopters of fashionable clothing may not be easily distinguishable as a market segment by demographic characteristics alone. Data and methods As noted earlier, the HES carried out by the Australian Bureau of Statistics in was the main source of data for this study. In this survey, a household was defined as a person or group of persons living together and having common provision for food and other essentials of living (Australian Bureau of Statistics 2000a). The scope of the survey included usual residents of private dwellings in Australia, except foreign diplomatic or defence force staff and people living in remote areas. The sample included 6,893 households throughout Australia. It was selected using a multistage, stratified probability sample design. Personal interviews were conducted in the selected households to obtain data on characteristics of households and their members, and various items of income and expenditure. In addition, identified spenders in the households were issued with a diary each to record expenditure on every item over the two weeks period immediately after the interview. In each household a person, aged 15 or over was selected as the reference person, if the person fulfilled one of the following criteria: was a partner in a registered or de facto marriage, or a lone parent with dependent child(ren), or the person with the highest income or the eldest person. In this paper we have designated such reference persons as the household heads. Appropriate weighting factors were assigned to each household to enable the estimation of the number, characteristics and expenditure patterns for all households in Australia. The sample was large enough to allow estimates for each State and Territory. The weighted estimates using the survey data have been reported as averages or counts. Information about the expenditure on mobile phones was recorded under expenditure code mobile phones, and code mobile phone accounts. Any household which reported expenditure under these items was considered as a user of mobile phones. It may be noted that in this study it is not possible to ANZMAC 2003 Conference Proceedings Adelaide 1-3 December

3 determine the total number of mobile phone users in Australia as it was only possible to identify households which had at least one mobile phone account. The other limitation of this study is that it only covered mobile phones which were paid for by the households. Thus, the phones paid for by the employers or businesses were outside the scope of this study. The market penetration rate for mobile phones was defined as the ratio: A i / B i, where A i was the number of households of characteristic i which had incurred expenditure on mobile phones, and B i was the total number of households with characteristic i. Characteristics of households According to the HES, of the estimated 7.12 million households in Australia in , only 2.66 million (37 %) had one or more mobile phones. Another survey, conduced over the four quarters in 1998, showed that the proportion of households which had access to mobile phones was 45 % (Australian Bureau of Statistics 2000b). The discrepancy in the two surveys is mainly because the HES did not include those households which had mobile phones paid for by the employers or businesses, as it could identify only those households which had incurred expenses on mobile phones. Table 1 presents selected socio-economic and demographic characteristics of households which reported having one or more mobile phones. It appears that the households headed by Generation-X had the highest proportion of mobile phone, followed by the Baby-boomers. Seniors had the lowest proportion. Further analysis revealed that there was a distinct negative gradient between the age cohort and income: average monthly income for the four age cohorts shown in Table 1 was $4013, $4787, $3278 and $1674 respectively. Although two-thirds of the households with mobile phones were headed by males, the market penetration rate for them was not much different from the female-headed households, despite the fact that the average monthly income for households headed by females was $ 2861 compared to $4400 for those headed by males. Country of birth and year of arrival in Australia indicated that the relatively recent migrants to Australia, and particularly those from Asia, were more likely to have mobile phones. The market penetration rate for European migrants was the lowest, partly because many of them were older. Country of birth is not necessarily a good indicator of ethnicity, as it excludes the Australian-born children of migrants. As expected, household heads which were in full-time employment had the highest, while the unemployed and those not in the labour force had the lowest proportion of mobile phones. Household income and the number of credit cards in the household had very strong positive associations with the propensity to have mobile phones. The highest market penetration rate was in the Australian Capital Territory, followed by New South Wales and Victoria, while Tasmania had the lowest rate. Table 1. Selected socio-economic and demographic characteristics of households with mobile phones Entrepreneurship, Innovation and Large and Small Business Marketing Track 899

4 Characteristics Households with mobile phone Percentage distribution of all Market penetration rate No. (000 s) % households per 1,000 HOUSEHOLD HEAD Age Cohort (birth year) Generation X (1964 or after) Baby-boomers ( ) 1, Pre-baby boomers ( ) Seniors (1932 or earlier) Gender Male 1, Female Country of birth Australia 1, Europe Asia Other Labor Force Status Employee - full time 1, Employee - part time Self employed Unemployed Not in the labour force HOUSEHOLD Income quintile First (bottom 20%) Third Fifth (top 20%) No. of Credit Cards None One Two Three or more State/Territory New South Wales Victoria Queensland South Australia Western Australia Tasmania Northern Territory Australian Capital Territory The number of dependent children in a household seemed to have a positive association with its likelihood of having a mobile phone. For households which had no dependent children in the age range 15-20, the market penetration rate was practically constant. However, as the number of dependent children increased, the market penetration rate also increased. The increase was much greater for households which had older dependent children as shown below: ANZMAC 2003 Conference Proceedings Adelaide 1-3 December

5 Age Age No dependents One dependent Two dependents Expenditure on mobile phones According to the HES, a household in Australia spent, on the average, $56.25 per month on mobile phones. Given that there were 2.66 million households with mobile phones, the total household expenditure on this product came to $1.796 billion during As pointed out earlier, our estimates do not include the commercial and business mobile phone accounts. Table 2. Expenditure on mobile phone by selected characteristics of households Characteristics of the household or its head Average monthly expenditure Total annual expenditure for all households per household $ $ (millions) % Age Cohort (birth year) Generation X (1964 or after) Baby-boomers ( ) Pre-baby boomers ( ) Seniors (1932 or earlier) Income quintile First (bottom 20%) Third Fifth (top 20%) Country of birth Australia , Europe Asia Other State/Territory New South Wales Victoria Queensland South Australia Western Australia Tasmania Northern Territory Australian Capital Territory Table 2 presents the average monthly expenditure on mobile phones per household and the total national expenditure according to selected characteristics of the households. It appears that household heads which belonged to Generation-X had the highest average expenditure on mobile phones, however, due to their size, Babyboomers constituted the largest segment of the market in terms of the total expenditure. There was no gender differential in the average expenditure on mobile phones Entrepreneurship, Innovation and Large and Small Business Marketing Track 901

6 As expected, the households with higher income had higher average expenditure on mobile phones. The households in the top income quintile accounted for 34 % of the total expenditure on mobile phones compared to 8 % for those in the lowest income quintile Households headed by non-european migrants spent, on the average, more money on mobile phones compared to other groups. The average monthly expenditure on mobile phones varied substantially between different parts of Australia. The highest average expenditure was in Northern Territory and lowest in Tasmania. The figure for the former was more than twice that for the latter. Conclusion During the past decade, the mobile phone industry in Australia has experienced significant changes in terms of its geographic coverage, introduction of new plans and technologies, and market penetration. This trend is likely to continue in future because of the convenience and immediacy of the technology. Many small enterprises and self-employed people increasingly use mobile phones as a replacement for backup office support. This study confirms the previous research findings that younger and affluent consumers are more likely to adopt new technologies, such as the mobile phones. From a managerial point of view it proposes some interesting basis for market segmentation. Our study shows that in addition to the widely used demographics (i.e., age and income), other variables such as the country of birth, household type in terms of number and age of dependent children, and the number of credit cards held by the household, could also be used as a basis for further market segmentation. Although this study is based on data collected 4-5 years ago, its findings could still be useful to marketers in identifying particular market segments that have and those that have not yet been exposed to the current and emerging telecommunication technologies. While this study does not provide information at the level of individual consumers, it does provide, for the first time in Australia, the demographics and expenditure patterns of households which had one or more mobile phones. It is recommended that further research of this type may be conducted using the existing databases of various mobile phone companies. References Australian Bureau of Statistics, 2000a, Household Expenditure Survey, Australia User Guide , ABS, Canberra. Australian Bureau of Statistics, 2000b, Household Use of Information Technology, ABS, Canberra. Australian Communications Authority, 2001, Telecommunications Performance Report, , ACA, Melbourne. Goldsmith, R & Flynn, LR 1992, Identifying innovators in consumer products markets, European Journal of Marketing, vol. 26, no. 12, pp ANZMAC 2003 Conference Proceedings Adelaide 1-3 December

7 Goldsmith, RE, d Hauteville, F & Flynn LR 1998, Theory and measurement of consumer innovativeness: a transitional evaluation, European Journal of Marketing, vol. 32, no. 3/4, pp Hirschman, EC 1980, Innovativeness, novelty seeking and consumer creativity, Journal of Consumer Research, vol. 7, no. 3, pp Im, S, Bayus, BL & Mason, CH 2003, An empirical study of innate consumer innovativeness, personal characteristics, and new-product adoption behavior, Journal of the Academy of Marketing Science, vol. 31, no. 1, pp Martinez, E, Polo, Y & Flavian, C 1998, The acceptance and diffusion of mew consumer durables : differences between first and last adopters, Journal of Consumer Marketing, vol. 15, no. 4, pp Midgley, D & Dowling, GR 1978, Innovativeness: the concept and its measurement, Journal of Consumer Research, vol. 4, no. 4, pp Pepermans, R, Verleye, G & Cappellen, SV 1996, Wallbanking, innovativeness and computer attitudes: year-old ATM users on the spot, Journal of Economic Psychology, vol. 17, no. 6, pp Roehrich, G 2002, Consumer innovativeness. Concepts and measurements, Journal of Business Research, vol. 57, no 19, pp. 1-7, viewed 28 June 2003, Available from Science Direct. Entrepreneurship, Innovation and Large and Small Business Marketing Track 903