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In a mature mobile phone market, dollars still drive consumers’ decisions, write Gennadi Kazakevitch, Luba Torlina and Sharon Hendricks.
In the wildly competitive business of high-tech there are few more crowded sectors than the mobile phone market. This mature market in Australia has largely exhausted possibilities for new entrants and reasonable customer base growth.
Brand new features are immediately uniform across the industry reducing the attractiveness of technological innovations, making price the major driver of competition rather than product differentiation and quality. Providers scramble for attention with frenetic advertising driven by aspirational imagery and carefully scripted pitches promising upgrades, or irresistible incentives to switch.
The Australian mobile phone market has been growing at an exponential rate over the last decade and today an amazing 77 per cent of the population have a mobile phone, making further growth very tough. Maintaining existing customers or indeed growing the customer base in a mature market is difficult.
Also a fascinating paradox develops in such markets, whereby product providers need to develop distinct strategies which allow them to compete effectively not only with their rivals, but with the earlier versions of their own products.
Consumer buying strategies become increasingly shaped by varied sets of product features and services, consumer switching costs, and network effects. These strategies complement traditional considerations of product utility and price. The key factors affecting consumer decisions should be considered by competing providers when they choose production and marketing strategies.
We empirically tested the youth mobile phone market to ascertain a model of consumers’ decision-making, based on common features of consumer behaviour in a mature high-tech market. The population which this study is based on is the Australian youth mobile phone market. For the purposes of the study, ‘youth’ is defined as those aged between 18 and 30. ‘Market’ is defined as those within the age range who own a mobile phone, as well as those considering purchasing a mobile phone.
The sample selected for this study consists of 120 university students approached on campus over a period of one week. The justification for the sample size is that such a size is sufficiently large for the purposes of parametric statistical analysis in general, and discriminant analysis in particular. The model is formulated on the assumption that a choice is to be made between continuing to use the existing version of the product, to upgrade it with the current provider or to switch to another provider.
The study is focused on typical properties of a mature high-tech market such as established customer and provider bases; very short product life cycle and considerable product differentiation. It found consumer switching costs, network effects and customer lock-in mechanisms to be the leading factors influencing both consumer choice and firms’ competitive strategies.
Consumer Switching Costs (CSCs) may include transaction, learning, artificial and contractual costs. Transaction costs are the costs incurred when a relationship with one supplier ceases before switching to a rival. Learning costs relate to the time spent learning how to use a new brand. The costs of switching both in terms of lost utility and money spent may outweigh any perceived benefits. Companies create artificial costs in order to increase customer loyalty.
The network effect is the positive effect of having so many other people also using that network. The challenge for companies seeking to introduce new technology that is not compatible with existing technology is to build network size and thus overcome the combined CSCs of all consumers.
Generally, consumer lock-in occurs where CSCs are higher than the perceived benefit of switching. There are several types of lock-in, including durable purchases, loyalty programs, brand-specific training, the absence or insufficiency of tools for converting data into different formats, and others.
The results revealed that overall, financial factors of product differentiation are more important for consumer decision making than technological components. The most important factor affecting the consumer behaviour is price. The second important category was specific financial factors such as designated time of day for free calls, free calls allowance and caps on monthly bills.
Within the network effect category, brand reputation, recommendation by an acquaintance and sports video highlights appear to have a significant influence on customer choice.
Understandably, the attitudes of the customer groups are rather different with regard to the switching costs. ‘Non-upgrading’ and ‘switching’ customers consider financial incentives, as well as the opportunity of trading in the old handset for cash, as the most important. Meanwhile switching between prepaid and contract service is most important for loyal customers and all customers see ‘lock-in’ as an important disincentive to switch.
Interestingly, time taken to learn how to use a new handset is not seen as a major obstacle nor were additional non-phone related gifts considered a major incentive.
Finally, handset specific quality factors like built-in camera, internet access and other additional accessories were not seen as important.
This approach might be applied to other mature markets of high technology and digital products with similar structures such as specialised software products, data management tools, accounting, mathematical and other professional packages as well as for practical decision-making and strategy-formulating by both consumers and producers.
Dr Gennadi Kazakevitch is Senior Lecturer in Economics at Monash University. One of the areas of his research interests and recent publications is economics of high technology and digital product markets.
Dr Luba Torlina is Lecturer in the School of Information Systems, Deakin University. Her recent publications include a number of articles on market structures and competition in the IT industries.
Sharon Hendricks is a recently graduated Monash University Faculty Business and Economics research student.
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URL: http://www.austlii.edu.au/au/journals/MonashBusRw/2005/23.html