Volume 12 Number 3 2004
SPECIAL ISSUE: Empirical Generalisation in Marketing
Special Issue Editors
Mark D. Uncles, School of Marketing, UNSW
Malcolm Wright, Robt. Jones Holdings Ltd
Listed below are the contents and the executive summaries from the latest issue of the Australasian Marketing Journal. The full papers can be accessed as PDF files free of charge at the AMJ website by clicking here
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Contents
5 Editorial
Empirical Generalisation in Marketing
Mark D. Uncles & Malcolm Wright
19 Executive Summaries (see below)
Papers
21 Consistent Consumer Responses To Price Changes
John Scriven and Andrew Ehrenberg (summary)
40 Dove vs. Dior: Extending the Brand Extension Decision-Making Process from Mass to Luxury (summary)
Francesca Dall’Olmo Riley, Wendy Lomax and Angela Blunden
56 The Stochastic Nature of Purchasing a State’s Lottery Products (summary)
Dick Mizerski, Rohan Miller, Katherine Mizerski and Desmond Lam
70 Brand and Advertising Awareness: A Replication and Extension of a Known Empirical Generalisation (summary)
Jenni Romaniuk, Byron Sharp, Samantha Paech and Carl Driesener
Research Notes
81 Testing Dick and Basu’s Customer Loyalty Model
Ron Garland and Philip Gendall
88 The Effect of Corporate Image in the Formation of Customer Loyalty: An Australian Replication
Allison E. Hart and Philip J. Rosenberger III
97 The Taiwanese are Just Like Australians in Their Loyalty to Fast Food Outlets
Dag Bennett
Book Reviews
104 Meaningful Marketing: 100 Data-Proven Truths and 402 Practical Ideas for Selling More With Less Effort
(Brain Brew Books: Ohio) by Douglas Hall and Jeffrey Stamp (2003)
Byron Sharp
106 Business and Management Research: How to Complete Your Research Project Successfully
(Westburn Publishers: Helensburgh, Scotland) by Michael J. Baker (2003)
Frank Alpert
110 Notes for Contributors
Executive Summaries
Consistent Consumer Responses To Price Changes
John Scriven and Andrew Ehrenberg
Textbooks often say or imply that each brand will have a characteristic price-elasticity, for example –1.8. Correspondingly, econometric models often specify a single regression coefficient for each brand’s price. But many practising pricing experts doubt this. Instead, price elasticities are thought to depend on the wider context (competitor prices, advertising perhaps, etc.) and not, or not only, on the brand itself. However, there is little comprehensive evidence in the literature to show which contextual factors lead consistently to higher or lower elasticity.
Our wide-ranging series of experiments confirm that brands do not have fixed elasticities, and show that there are factors that consistently lead to higher or lower elasticity across conditions such as countries, products, and brands. We identify five contextual factors and three consumer related factors that consistently lead to bigger price elasticity. For example, how closely competitive prices are to start with and whether a brand passes the price position of other brands with the change. Consumers who are younger classify themselves as more price conscious, and consumers who are light buyers of the brand have bigger elasticity.
We also found several factors that do not seem to affect elasticity consistently. Some of these factors are perhaps quite surprising, such as that advertised brands did not have bigger elasticity (once size was taken into account), nor did lower income consumers.
Most of our findings tie in well with the existing previously isolated results in the literature, and go some way towards identifying the more important elements influencing variations in response to price changes. The well-established notion that consumers use reference points in price-related decision making comes through strongly in all the results, and an important point to emerge is the need for further research into how consumers combine the various reference structures that are available to them.
For those who have to make pricing decisions, the study provides a set of benchmarks that can suggest which factors to consider in changing a price (for example, the importance of passing a competitor’s price or not), and against which to evaluate their own past and future results.
Dove vs. Dior: Extending the Brand Extension Decision-Making Process from Mass to Luxury
Francesca Dall’Olmo Riley, Wendy Lomax and Angela Blunden
Few articles have examined how managers choose whether to launch a new product as a line extension or as a second brand, or the decision process underlying such decisions. Furthermore, little research has sought to establish whether managers’ decision process concerning brand extensions and the factors underlying such decisions are the same in different industries and for products and brands with different characteristics. For example, while brand and line extensions are widespread within both the mass-market fast moving consumer goods sector and the luxury goods industry, we know little about the strategic antecedents, decision criteria and launch judgement process across these different markets and circumstances.
This paper examines the decision process used by luxury goods managers when extending their brands. In particular, we investigate whether the process model of extension decisions put forward by Ambler and Styles (1997) for fast moving consumer goods can be stretched to the luxury sector environment. The present study can be viewed as an attempt to see where the earlier model generalises and where it needs to be contextualised.
We find that the general structure of the brand extension decision process remains the same for fast moving and luxury goods (in terms, for example, of antecedents, decision-criteria and launch), but specific elements such as tradition, heritage and craftsmanship are key – and distinctive – considerations before deciding to extend a luxury brand. Furthermore, luxury goods experts recognise the importance of after-sales service in supporting the launch of luxury brands extensions.
The Stochastic Nature of Purchasing a State’s Lottery Products
Dick Mizerski, Rohan Miller, Katherine Mizerski and Desmond Lam
State Lotteries have significant effects on those state’s revenues, their residents’ behaviours and their ultimate welfare. Impressive sales figures for schemes such as six-number Lotto and Instant (scratch-off) games are backed by sophisticated marketing and promotion budgets. This study of reported lottery product purchasing suggests high levels of habitual behaviour, the key aspects of which can be described by simple stochastic models of buyer behaviour.
For lottery marketers, the implications of stochastic preference primarily influence the relative effect of the marketing mix through the gambling product’s Product Life Cycle. Given the high level of habit exhibited in game purchase for the lottery schemes studied, the ability of advertising and promotion to affect the aggregate size of the market is questionable beyond the early stages of the PLC. Distribution appears to be the most important of the mix factors, perhaps even more important than jackpot size.
A strong habit-driven consumer franchise presents some public policy challenges. To the extent that cognitive-based information processing is limited, the role of warning information about addiction and its manifested problems would appear to be of little influence. Efforts to address buyer misconceptions about the random nature of the game would also be compromised by habitual buying.
The area of stochastic models may offer policy makers more appropriate tools to judge when game play deviates from the “normal” purchase patterns expected. Use of these “baseline” measures needs more validation, but they may offer more accurate measures than the present instruments, when judging an acceptable level of compulsive play in a population.
Brand and Advertising Awareness: A Replication and Extension of a Known Empirical Generalisation
Jenni Romaniuk, Byron Sharp, Samantha Paech and Carl Driesener
Awareness measures (top of mind, spontaneous and aided) are commonly used marketing metrics in both the brand and advertising domains. However, little is known about how the different measures relate to each other. This research shows that specific awareness measures may be more important for larger than for smaller brands. For example, with larger brands aided awareness is typically stable, whereas spontaneous (unaided) awareness can vary considerably. By contrast, with small brands spontaneous awareness measures are typically stable, and it is the aided awareness scores that vary.
Knowing this provides insight into which measure is more useful for managers to watch. We recommend that the more stable statistic should be the focus of management attention; for these statistics variation is unusual and therefore, when there is some variation, it is likely to indicate real market changes rather than be the result of sampling variation.
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