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July 19, 2010

How Wealth and Need-for-Status Influence Consumer Behavior Toward Luxury Goods

The article authored by Young Jee Han, Joseph C. Nunes, and Xavier Drèze (“Signaling Status with Luxury Goods: The Role of Brand Prominence”) in the July 2010 issue of JM provides rich insights into consumers’ perceptions of and responses to luxury goods. The authors propose a simple, intuitive, and interesting taxonomy that assigns consumers to one of four groups in a 2 x 2 grid—namely, wealth (haves and have-nots) and need for status or NFS (high and low). Each of these groups differs in terms of their predispositions to associate or dissociate with members of their own and other groups. In turn, these differences produce testable hypotheses about the behavior of each group toward conspicuous (loud) or inconspicuous (quiet) luxury goods, a construct that the authors call “brand prominence.”

More specifically, the four groups in the taxonomy include patricians (haves and low NFS), parvenus (haves and high NFS), poseurs (have-nots and high NFS) and proletarians (have-nots and low NFS). The patricians are motivated to associate with or signal to other members of their own group; the parvenus associate with patricians and with other members of their own group, but dissociate with poseurs and proletarians; the poseurs actively associate with patricians and parvenus; and the proletarians do not engage in any form of association or dissociation (i.e., no status signaling).

In a series of four studies, the authors empirically verify the following:

(1) Quiet luxury goods are priced higher than loud luxury goods produced by the same manufacturer, a finding compatible with the view that patricians are willing to pay a premium for the former;

(2) Lower-priced and loud luxury goods tend to be copied more by counterfeiters than other brands in the same product line, a result in line with the expectation that counterfeiters cater primarily to poseurs seeking to follow parvenus;

(3) Patricians are capable of deciphering subtle brand cues in luxury brands; and

(4) Preferences for loud and quite luxury goods differ across the four groups in line with each group’s distinctive pattern of associations and/or dissociations with other groups.

Overall, this research article marks a great beginning in a promising and new area. I found the discussion on griffe (“a set of special signatures” for the brand) especially illuminating. The authors are careful to recognize the limitations of their study and offer intriguing suggestions for future research. This study focuses attention on luxury goods, but it may be worthwhile to explore any limits to generalizing this framework to luxury services.

As always, I encourage JM readers to share your thoughts on this interesting article. Your contributions will help us advance the discussion.

Siva K. Balasubramanian, Web Editor, Journal of Marketing

July 14, 2010

Gap Between Program and Commercial Audiences

The May 2010 issue of JM includes an interesting study by David Schweidel and Robert Kent (“Predictors of the Gap Between Program and Commercial Audiences: An Investigation Using Live Tuning Data”). This article showcases the advertiser’s challenges and information needs and underscores the limitations in the data currently available to the advertiser to make informed decisions about television advertising.

More specifically, the study breaks new ground in two respects. First, unlike previous work, the authors simultaneously consider program-related and commercial-related tuning. Their focus is to assess and analyze the gap between the audience exposed to programs and the audience exposed to commercials. The former reflects the popularity of the program and the latter captures ad avoidance behaviors. The authors note that the key problem advertisers face is when ad pricing is tied to program ratings. This is because programs not only differ on ratings but also vary in terms of ad avoidance audience behavior.

Second, this research uses a full television season’s worth of live tuning data (collected from digital cable set-top boxes in a major metropolitan area). The rich and longer time frame and scope of the data analyzed allow the authors to incorporate show-specific random effects. This study feature shows that programs may produce appeals or ad avoidance outcomes that are quite different from what their characteristics would suggest.
The authors recognize the limitations inherent in the live tuning approach (i.e., it only captures the potential for exposure to programming and commercials) as opposed to more hard-nosed measures of actually documented exposure or audience engagement.

Overall, given the complexity of the choices facing advertisers (to buy exposure) and networks (to sell exposure) and the real paucity of useful and actionable date to make these choices, the data and analyses reported present a new direction that both advertisers and networks will find useful. The authors note several areas in which this research stream could be advanced further.

As always, I welcome readers’ inputs and comments on this JM article.

Siva K. Balasubramanian, Web Editor, Journal of Marketing

Empirical Findings on “Rule of Three”

The article by Can Uslay, Z. Ayca Altintig, and Robert Winsor (“An Empirical Examination of the ‘Rule of Three’: Strategy Implications for Top Management, Marketers, and Investors”) in the March 2010 issue of JM is thought provoking. This study breaks new ground by empirically testing the “Rule of Three” proposed by Sheth and Sisodia that suggests that both strategic focus (generalist vs. specialist) and market share are related to firm performance.

A generalist is defined as a firm that “serves the general market with a full line of offerings and has 10%–40% or higher market share” (p. 21). In contrast, a specialist firm focuses on a market niche and has a market share below 5%. The Rule of Three specifically advances the following views or hypotheses: (1) In general, the competitive structure in mature industries is controlled by three generalist firms, (2) industries with three generalists perform better than those with a fewer or greater number of generalists, (3) both generalist and specialist firms perform better than firms that fall somewhere in between in terms of strategic focus, (4) the performance advantages stemming from market leadership diminish when market share is large, and (5) the financial markets are yet to fully recognize/acknowledge the Rule of Three and its influence over firm performance.

The authors augment the Rule of Three using ecological resource partitioning theory and industrial organization theory to advance formal hypotheses. Using COMPUSTAT/CRSP databases from 1997 and 2002, they present tests of several performance outcome measures: oROA, or operating return on assets; three-year oROA; CAR, or cumulative abnormal return; three-year CAR; and price–earnings ratio. Their empirical analyses support the hypotheses. Given potential definition problems and/or specific data characteristics or operationalizations, I found the authors’ attention to robustness checks to be especially impressive. In other words, they took special care to rule out the likelihood that the results were idiosyncratic to the manner in which the variables were operationalized.

The implications discussed with regard to the investor community are especially intriguing. For example, the authors argue that firms with a strategic focus between the generalist and the specialist (i.e., the ditch dwellers) may not be good long-term investments but could be excellent speculative investments.

As always, the views of JM readers on this featured article and this blog are most welcome. Your contributions help us advance research discussion for the benefit of our discipline.

Siva K. Balasubramanian, Web Editor, Journal of Marketing

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