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Cyber‐brands are regularly valued but, to date, there has been no reported research designed to understand the derivation of cyber brands’ equity, so that attempts can be made to increase their brands’ equity efficiently. This research aims to address the issue.

To measure the strength of cyber brands, prior off‐line research is replicated, taking a customer focus to identify determinate variables. These customer‐focused variables are tested against cyber consumers’ stated satisfaction and site‐visit intention behavior, using regression analysis.

The results satisfactorily justify the suggested model, which has a predictive power ranging from 62 to 72 per cent.

The study shows that practitioners intent on raising the power of their cyber brand can be guided by the same model as used off‐line.

The major theoretical contribution of the study is to show that there is little difference between measuring and increasing brand power on or off‐line.

Decision system analysis is a conceptually simple technique that maps the process of group decisions over time. The data is gathered in a variety of ways, but most often some form of protocol analysis is the foremost tool. The data is then condensed and depicted as a flowchart for a specific decision. If several such flowcharts can be assembled within an industry, they can be melded together to form a generic guide that is very useful to practitioners and very interesting to theorists. Here, a brief history of the development of the technique leads to a description of the process. This is followed by a comparison to cognitive mapping (a similar technique applied to mapping thought processes rather than physical processes), and an illustrative longitudinal example of DSA.

The purpose of this paper is to report the use of decision system analysis (DSA) mapping the streams of communications (i.e. interactions), thoughts, actions and decisions involved for advertising agencies as executives in these firms gain client approval, and design creative, promotional and media strategies.

This study uses DSA. This little‐used technique requires protocol analysis, interviews and observation before transcription of the organizational decision processes into flow charts.

The research first identifies four models, describing four specific decision types, then derives a general model from them. Executives from four agencies not in the original sample later confirms the models. The models generally confirm the existing knowledge base, with a few minor exceptions.

This qualitative technique suffers the common malady of the researchers losing objectivity because of their immersion in the case‐companies. Wherever possible the research employs quantitative techniques to verify observational judgments.

The “thick description” and the summary charts of the advertising agency decision processes have the potential to aid agency decision makers to better structure their decision processes.

The findings themselves are of significance to those involved in the advertising industry, and there is an element of originality in the classification and the thick descriptions of advertising agency decision systems. The resurrection of DSA and the demonstration that the technique is viable and valuable is also a contribution of the study.

In most markets it is possible to identify a brand leader and a number of brand followers. The purpose of this paper is to address the following question: “Why should any consumer purchase a ‘second‐best’ option?”

Consideration of the way in which these two groups of consumers (brand leaders and followers) trade off product attributes (utilitarian benefits, hedonistic benefits and price fairness) during the choice process is made in the study by path analysis of the appropriate structural equation models and then a consideration of the level and the differences between the means of the three variables.

The paper finds that utilitarian attributes are of paramount importance to satisfaction with the brand. This is not in accordance with conventional wisdom, which leads us to believe that price is most important to buyers of second‐tier brands and hedonic considerations most important to buyers of leading brands.

The model fit attained is only good enough for exploratory work (GFI =0.88/0.90) so replication with a larger sample would be appropriate. In addition, the research is carried out in South Korea – although we know of no reason why this should affect the results it would be of interest to generalize the results to a western economy. Nevertheless, the method of first fitting the model then trading off the attribute levels is unusual and quite interesting.

Marketers of leading brands should not concern themselves about price but merely stress the benefits, whereas marketers of follower brands should make much of the price differential.

The importance of utilitarian benefits have hitherto not often been stressed when marketing premium brands – this research suggests that this is wrong.

Extant research on comparative advertising has focused only on “market leader” comparisons (a brand targeting the market leader), whereas in the marketplace, “multi-brand” comparisons are more prevalent (Kalro et al., 2010). Moreover, most research focuses on direct comparisons only. Hence, this research aims to investigate the interplay between comparison ad strategy (“market leader”/“multi-brand” comparisons) and comparison ad format (direct/indirect comparisons) on the effectiveness of comparative advertising.

This paper uses four 2 × 2 fully crossed factorial designs (comparison ad format: direct vs indirect and comparison ad strategy: market leader vs multi brand) with established and new brands in two categories: powdered detergents and smart phones. All studies were conducted in metropolitan cities of India.

By and large, the experiments indicated that direct (indirect) comparisons lowered (heightened) perceived manipulative intent and enhanced (reduced) attitude-toward-the-ad for multi-brand (market leader) comparisons.

Findings suggest that when advertisers use comparative advertising, they may use direct ads when using multi-brand comparisons and use indirect ones when using market leader comparisons. It could also be argued that when advertisers use multi-brand comparisons because of fragmentation in the marketplace, they may directly compare against these multiple brands. When advertisers need to compare against a market leader, they may do so indirectly.

This research is among the first to investigate multi-brand comparisons that are widely used in the industry and that too in the context of both direct and indirect comparison formats.