Conference Sessions - Jesse H. Jones Graduate School of ...
Conference Sessions - Jesse H. Jones Graduate School of ...
Conference Sessions - Jesse H. Jones Graduate School of ...
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Thursday, 3:30pm - 5:00pm<br />
■ TD01<br />
Legends Ballroom I<br />
Choice II: Effects on ...<br />
Contributed Session<br />
Chair: Linda Court Salisbury, Assistant Pr<strong>of</strong>essor, Boston College, CSOM,<br />
Fulton 441, 140 Commonwealth Ave., Chestnut Hill, MA, 02467, United<br />
States <strong>of</strong> America, salisbli@bc.edu<br />
1 - Incorporating State Dependence in Aggregate Market<br />
Share Models<br />
Polykarpos Pavlidis, PhD Candidate, Simon <strong>Graduate</strong> <strong>School</strong> <strong>of</strong><br />
Business, University <strong>of</strong> Rochester, Rochester, NY, 14627,<br />
United States <strong>of</strong> America, pavlidisp2@simon.rochester.edu,<br />
Dan Horsky, Minjae Song<br />
An empirical investigation <strong>of</strong> individual household level data in twenty CPG<br />
categories (IRI Marketing Data set, 2008) uncovers that state dependence is a<br />
significant determinant <strong>of</strong> consumers’ choices in all twenty product categories. In<br />
light <strong>of</strong> this finding, we examine whether and how one can incorporate state<br />
dependence in a demand model <strong>of</strong> frequently purchased goods estimated with market<br />
level data. Aggregated data is more <strong>of</strong>ten available and is frequently used in applied<br />
research in marketing and economics. The incorporation <strong>of</strong> consumer choice<br />
dynamics in these market share models can potentially increase their applicability and<br />
improve their predictive behavior.<br />
2 - Complexity Effects on Choice Experiment-based<br />
Model Performance<br />
Benedict Dellaert, Erasmus University Rotterdam, P.O. Box 1738,<br />
Rotterdam, 3000 DR, Netherlands, dellaert@ese.eur.nl,<br />
Bas Donkers, Arthur van Soest<br />
Understanding what drives choice experiment-based model performance helps firms<br />
to better evaluate future marketing actions when using such models. This research<br />
investigates choice experiment complexity (i.e., the number <strong>of</strong> alternatives, number<br />
<strong>of</strong> attributes, and utility similarity between the most attractive alternatives) as a key<br />
factor to affect choice model performance both within and between complexity<br />
conditions. The results show that complexity has a negative direct effect on choice<br />
model performance. However, this effect is contingent on consumers’ decision time<br />
used relative to the number <strong>of</strong> normative elementary information processes (EIPs)<br />
that the decision task requires, which we take as an approximation <strong>of</strong> the degree <strong>of</strong><br />
simplification in the consumer’s decision process. When consumers spend less time<br />
per normative EIP, this increases choice model performance within a given choice<br />
complexity condition. However, it decreases choice model performance between<br />
complexity conditions. We also introduce a practical modeling approach that captures<br />
these direct and indirect effects <strong>of</strong> choice complexity and hence enables predictions<br />
between different choice complexity conditions.<br />
3 - The Interplay <strong>of</strong> Reference Dependence and Choice Set Formation in<br />
Replacement Decisions<br />
Lianhua Li, PhD Student, University <strong>of</strong> Alberta, Faculty <strong>of</strong> Business,<br />
Edmonton, AB, Canada, lianhua@ualberta.ca, Paul Messinger,<br />
J<strong>of</strong>fre Swait<br />
The literature presents evidence supporting the expectation <strong>of</strong> a strong preference for<br />
the status quo good in replacement decisions. Prospect theory predicts this tendency;<br />
however, prospect theory ignores possible choice set formation effect, assuming that<br />
all goods (status quo and new goods) will be evaluated, using the status quo as<br />
reference point, and then compared to reach a final choice. Nonetheless, several<br />
explanations for the exaggerated preference for status quo goods in prior literature<br />
predict the possibility <strong>of</strong> choice set formation revolving around status quo products.<br />
We therefore hypothesize that replacement decisions are subject to both referencedependence<br />
and choice set formation effect. To test this hypothesis, we develop and<br />
compare three choice models: a pure reference-dependence model, a pure choice set<br />
formation model, and a hybrid model that accounts for both reference-dependence<br />
and choice set formation. Using experimental choice data, we find that the hybrid<br />
model greatly outperforms the first two models, which strongly suggests the<br />
coexistence <strong>of</strong> reference-dependence and choice set formation in replacement<br />
decisions. We also show that omitting either process leads to estimation bias in the<br />
parameters <strong>of</strong> the included process. Just as the reference-dependence model based on<br />
prospect theory has led to improved understanding and prediction <strong>of</strong> choice, we<br />
believe “upgrading” it to include choice set formation effect will further enhance<br />
these benefits.<br />
4 - Does Choice Set Formation Drive the Diversification Effect?<br />
A Model and Experimental Evidence<br />
Linda Court Salisbury, Assistant Pr<strong>of</strong>essor, Boston College, CSOM,<br />
Fulton 441, 140 Commonwealth Ave., Chestnut Hill, MA, 02467,<br />
United States <strong>of</strong> America, salisbli@bc.edu, Fred M. Feinberg<br />
Diversification – exhibiting greater variety as multiple choices are made together, in<br />
advance <strong>of</strong> consumption – is a robust and important phenomenon (e.g., purchasing<br />
groceries, queuing Netflix films). Studies <strong>of</strong> diversification tend to focus on choice<br />
alone, conceptualizing it as inherently comparative. This precludes the possibility that<br />
diversification is driven largely by choice set formation, wherein each item needs to<br />
27<br />
MARKETING SCIENCE CONFERENCE – 2011 TD02<br />
surpass a (latent) threshold to even be compared with others available. We examine<br />
diversification via an experimental choice sequence task and dual-component<br />
stochastic model (choice set formation; choice-from-set). The experiment manipulates<br />
two key diversification drivers in prior literature: whether choices are made all at<br />
once (“simultaneously”) vs. separately (“sequentially”), and the relative attractiveness<br />
<strong>of</strong> available options. We find that diversification may be primarily a phenomenon <strong>of</strong><br />
choice set formation: people do penalize their previously chosen option, but only for<br />
simultaneous choices, and only in the set formation portion <strong>of</strong> the model. Thus, prior<br />
model-based evidence <strong>of</strong> variety-seeking in diversification may have been<br />
misinterpreted as a discounting <strong>of</strong> an item’s features at the stage <strong>of</strong> choice, as opposed<br />
to a failure to ‘consider’ the option at all. That is, failing to methodologically<br />
incorporate choice set formation may erroneously suggest that consumers are using a<br />
diversification choice heuristic when they may instead be diversifying the alternatives<br />
in their ‘consideration set.’ Furthermore, results suggest that the expected number <strong>of</strong><br />
items thus ‘considered’ is substantially greater in multiple-, versus single-, item<br />
choice.<br />
■ TD02<br />
Legends Ballroom II<br />
Online Advertising - II<br />
Cluster: Internet and Interactive Marketing<br />
Invited Session<br />
Chair: Harald van Heerde, University <strong>of</strong> Waikato, Private Bag 3105,<br />
Hamilton, 3240, New Zealand, heerde@waikato.ac.nz<br />
1 - Connecting Social Media with Television Advertising and<br />
Online Search<br />
Yanwen Wang, PhD, Emory University, 1300 Clifton Rd,<br />
Atlanta, GA, 30033, United States <strong>of</strong> America,<br />
yanwen_wang@bus.emory.edu<br />
In an attempt to muscle through turbulent economic times, the U.S. automobile<br />
industry has embraced social media. Ford pioneered the practice <strong>of</strong> hiring syndicated<br />
bloggers to serve as brand advocates, while much <strong>of</strong> BMW’s recent success is<br />
attributed to its engagement with consumers across Facebook, Twitter, and YouTube.<br />
While there is research looking at the impact <strong>of</strong> social media on firm outcomes – be<br />
they sales or other metrics like stock-returns – little, if any, research is undertaken on<br />
understanding how social media impact consumers’ online search for automobiles.<br />
Understanding the impact <strong>of</strong> social media on consumer search is very important as<br />
online search informs consumer’s consideration-sets, which in turn affect their final<br />
choice <strong>of</strong> an automobile. By combining three unique datasets, namely: (i) consumerlevel<br />
click-stream search data for automobiles, (ii) consumer-directed television<br />
advertising and (iii) social media (volume and sentiments <strong>of</strong> buzz spanning blogs,<br />
newspaper articles, newsgroups, online forums, etc.), this study sets out to answer<br />
the following questions. One, how does the volume and sentiment <strong>of</strong> online buzz<br />
impact the volume <strong>of</strong> a consumer’s online branded search? Two, how do these effects<br />
compare with the impact <strong>of</strong> television advertising on online search? Three, are there<br />
synergies between online buzz and television advertising on online search? How do<br />
these effects systematically vary across consumers and geographic markets? After<br />
calibrating our model with these aforementioned data, we <strong>of</strong>fer insights for<br />
advertising and targeted advertising interventions to undo negative buzz generated<br />
through product recalls.<br />
2 - Investigating Advertisers’ View <strong>of</strong> Online and Print Media:<br />
Complements or Substitutes?<br />
Shrihari Sridhar, Assistant Pr<strong>of</strong>essor <strong>of</strong> Marketing, Michigan State<br />
University, Eli Broad College <strong>of</strong> Business, N300 Marketing<br />
Department, East Lansing, MI, 48824, United States <strong>of</strong> America,<br />
sridhar@bus.msu.edu, S. Sriram<br />
Faced with declining pr<strong>of</strong>its, print newspapers have turned hybrid, catering to both<br />
print and online audiences. As a multi-channel platform, the hybrid newspaper needs<br />
readers and advertisers across both print and online channels to be on board. This<br />
requires knowledge not only about the interrelatedness in demand between readers<br />
and advertisers, but also about whether advertisers perceive the print and online<br />
media-channels to be complements or substitutes. Extant research has investigated<br />
whether readers find online and print newspapers to be complements or substitutes.<br />
But less is known about how advertisers, who provide 80% <strong>of</strong> newspaper revenue,<br />
choose to allocate their media dollars between the online and print version <strong>of</strong> a<br />
multi-channel platform. From a newspaper’s standpoint, understanding advertisers’<br />
preferences for allocating advertising expenses between print and online media would<br />
be useful to develop targeted pricing and salesforce strategies. We use advertiser-level<br />
data from a large hybrid newspaper in the US from 2005-2010, pertaining to the<br />
amount <strong>of</strong> media dollars purchased across three outlets (print-weekday, print-Sunday<br />
and online) by quarter. We estimate a multiple discrete-continuous extreme value<br />
model (MDCEV) <strong>of</strong> advertisers’ simultaneous choice (i.e., which combination <strong>of</strong><br />
media to advertise in) and the corresponding expenditure in each medium. While<br />
performing this analysis, we control for temporal variation in print and online<br />
readership as well as salesforce efforts directed at each advertiser. We subsequently<br />
investigate how this decision is affected by advertisers’ baseline utility for each<br />
medium, growth in the readership base across channels and also by their perceived<br />
substitutability/complementarity across channels.