Ye Hu

Resistance to Brand Switching When a Radically New Brand Is Introduced: A Social Identity Theory Perspective.

There has been little research on how market disruptions affect customer–brand relationships and how firms can sustain brand loyalty when disruptions occur. Drawing from social identity theory and the brand loyalty literature, the authors propose a conceptual framework to examine these issues in a specific market disruption, namely, the introduction of a radically new brand. The framework focuses on the time-varying effects of customers’ identification with and perceived value of the incumbent relative to the new brand on switching behavior. The authors divert from the conventional economic perspective of treating brand switching as functional utility maximization to propose that brand switching can also result from customers’ social mobility between brand identities. The results from longitudinal data of 679 customers during the launch of the iPhone in Spain show that both relative customer–brand identification and relative perceived value of the incumbent inhibit switching behavior, but their effects vary over time. Relative customer–brand identification with the incumbent apparently exerts a stronger longitudinal restraint on switching behavior than relative perceived value of the incumbent. The study has important strategic implications for devising customer relationship strategies and brand investment.

An Analysis of Real World TV Advertising Tests: A 15-Year Update

ABSTRACT An analysis is performed on the results of 241 real world TV advertising tests conducted by Information Resources, Inc. between 1989 and 2003 to partially update the findings of Lodish et al. [Journal of Marketing Research 32, 2 (1995): 125–39]. Two types of market test results, BehaviorScan and Matched-Market, are analyzed. Overall, the improvement of TV advertising sales effectiveness because of media weight increase is significantly larger than zero for established products, which is different from Lodish et al.s finding. A further analysis indicates that such significance is mainly driven by more recent tests. A comparison between the new results and Lodish et al. reveals a significant increase in the average advertising effectiveness for tests completed after 1995. The new data still suggest (as did the original data) that it is of great managerial interest to identify advertising effectiveness before launching advertising campaigns.

Decomposing the Impact of Advertising: Augmenting Sales with Online Search Data

Unlike sales data, data on intermediate stages of the purchase funnel (e.g., how many consumers have searched for information about a product before purchase) are much more difficult to acquire. Consequently, most advertising response models have focused directly on sales and ignored other purchase funnel activities. The authors demonstrate, in the context of the U.S. automotive market, how consumer online search volume data from Google Trends can be combined with sales data to decompose advertisings overall impact into two underlying components: its impacts on (1) generating consumer interest in prepurchase information search and (2) converting that interest into sales. The authors show that this decompositional approach, implemented through a novel state-space model that simultaneously examines sales and search volumes, offers important advantages over a benchmark model that considers sales data alone. First, the approach improves goodness-of-fit, both in and out of sample. Second, it improves diagnosticity by distinguishing advertising effectiveness in interest generation from its effectiveness in interest conversion. Third, the authors find that overall advertising elasticity can be biased if researchers consider only sales data.

Modeling behavioral regularities of consumer learning in conjoint analysis

In this note, the authors propose several extensions of the model of consumer learning in conjoint analysis that Bradlow, Hu, and Ho (2004) develop. They present a clarification of the original model, propose an integration of several new imputation rules, add new measurement metrics for pattern matching, and draw a roadmap for further real-world tests. The authors also discuss general modeling challenges when researchers want to mathematically define and integrate behavioral regularities into traditional quantitative domains. They conclude by suggesting several critical success factors for modeling behavioral regularities in marketing.

An Update of Real-World TV Advertising Tests

ABSTRACT An analysis is performed on the results of 50 recent real-world TV advertising tests conducted by Information Resources, Inc. to update the findings of Lodish et al. [Journal of Marketing Research 32, 2 (1995): 125–39] and Hu, Lodish, and Krieger (Hu et al.) [Journal of Advertising Research 47, 3 (2007): 341–53]. Overall, the improvement of TV advertising sales effectiveness from media weight increase is significant for established products, consistent with Hu et al.s finding based on tests completed after 1995, further confirming that TV advertising effectiveness has improved during recent years. The new results continue to confirm that using valid and reliable pretests to assess TV advertising effectiveness should be an important practice in the industry.

How do external reference prices influence online gift giving

The authors examine the role of external reference prices in a unique form of gift giving behaviour - online gift registries. A hierarchical Bayesian analysis of fulfilment data from 555 online wedding registries reveals the probability of a gift fulfilment follows a bimodal distribution around the gift registrys average price. This is consistent with the hypothesis that online gift purchases are driven by the average price of the registry, which serves as the reference price, and two competing motivations among gift givers. These motivations are a desire for social benefits (e.g., to enhance the relationship) and a desire to limit monetary costs (e.g., to save money). The former motivation favours gifts with higher than average prices; whereas the latter favours those with lower than average prices. Because an average priced gift does not appeal to either segment, its fulfilment probability is relatively low. Finally, because gifts with extremely high or extremely low prices have less appeal for each segment, the fulfilment probability curve is bimodal.

The Role of Reference Price in Gift Registry Fulfillment: Empirical and Experimental Evidence

The authors examine the role of reference prices in a unique form of gift giving behavior - gift registries. A Hierarchical Bayesian analysis of fulfillment data from 555 online wedding registries and results from a laboratory experiment reveal that gift fulfillment probability follows a bimodal distribution around the average price of a gift registry. This is consistent with the hypothesis that gift purchases in the context of gift registries are driven by the average price of the registry, which serves as the reference price, and two competing motivations among gift givers: a desire for social benefits (e.g., to enhance relationship) and a desire for monetary benefits (e.g., to save money). The former motivation favors gift items with higher than average prices whereas the latter favors those with lower than average prices. This finding is robust after controlling for gift budget and relationship with the recipient. Our analysis also indicates that higher reference prices in the form of average price of the registry increase total gift spending from a registry, but only when gift givers are casual acquaintances to the recipient.