In today’s market, developing the tools needed to make informed marketing decisions and execute successful marketing strategies is key. The Marketing concentration focuses on developing new products, conducting market research, planning advertising and promotion programs, creating marketing strategies, providing superior customer service, understanding e-commerce, developing profitable pricing strategies, and brand management
Assistant Professor Mike Palazzolo’s research examines how consumers make intertemporal trade-offs. He has two streams of research stemming from this over-arching interest. The first explores consumer search behavior and the trade-off between short-term effort and long-term outcomes. The second explores consumer financial decision making and the trade-off between short-term expenditure and long-term savings.
540 Alumni Ln
Households commonly use strategies that provide long-term savings for everyday purchases in exchange for an increase in their short-term expenditures. They buy larger packages of nonperishable goods to take advantage of bulk discounts, and accelerate their purchases to take advantage of temporary discounts.
Modeling Consideration Set Substitution
Working Paper (Revising for invited resubmission with Marketing Science)
Consumers purchasing from a large set of alternatives often evaluate only a subset-a consideration set-in order to balance the expected benefits from search (e.g., finding a high-quality product) with costs (time, etc., needed to make a choice). If the marginal expected benefit from search decreases in the number of considered alternatives, marketing actions that encourage consideration of one alternative may discourage consideration of another.
Research Expertise: Marketing and advertising strategy, integrated marketing communications, and dynamic market response models, including preparing for product harm crisis
Research Expertise: Competitive strategy, game theory and applied optimal control
Research Expertise: Marketing research, marketing science, decision and management sciences, consumer choice behavior, choice modeling, new product development and introduction
Professor David Bunch is an internationally recognized expert on marketing research, marketing science and decision and management sciences. His research interests include consumer choice behavior, choice modeling, new product development and introduction, travel behavior, vehicle choice and alternative fuel vehicles.
Impact of Social Network Structure on Content Propagation: A Study Using YouTube Data
Quantitative Marketing and Economics, 2012
In this study, Assistant Professor Hema Yoganarasimhan examines how the size and structure of the local network around a node affects the aggregate diffusion of products seeded by it in the context of YouTube, the popular video-sharing site.
Bayesian Analysis of Random Coefficient Logit Models Using Aggregate Data
Journal of Econometrics, 2009
In this paper, Assistant Professor Renna Jiang and co-authors Puneet Manchanda from the University of Michigan Ross School of Business and Peter E. Rossi from the UCLA Anderson School of Management present a Bayesian approach for analyzing aggregate level sales data in a market with differentiated products.
Information, Learning, and Drug Diffusion: The Case of Cox-2 Inhibitors
Quantitative Marketing and Economics, 2009
The recent withdrawal of Cox-2 Inhibitors has generated debate on the role of information in drug diffusion: can the market learn the efficacy of new drugs, or does it depend solely on manufacturer advertising and FDA updates?
In this study, Assistant Professor Renna Jiang and co-authors Pradeep K. Chintagunta from the University of Chicago and Ginger Z. Jin from the University of Maryland use a novel data set to study the role of learning in the diffusion of three Cox-2 Inhibitors—Celebrex, Vioxx and Bextra—before the Vioxx withdrawal.
Professor Prasad Naik discusses how research and teaching complement each other, where students benefit from his research and he benefits from their ideas, input and feedback. “What I teach I bring it back into my research; what I research I bring it back into the classroom. Research and teaching are two sides of the same coin.”
Research Expertise: Advertising allocation models, direct to consumer marketing, dynamics of customer behavior and loyalty, time series analysis in marketing, dynamic advertising models, and spatiotemporal models
540 Alumni Lane
What is the optimal advertising budget and allocation that maximizes profits across multiple regions and over time? The chief marketing officer of a Fortune 500 company raised the question after she noticed that increasing her company’s advertising expenditures enhanced sales as expected, while profits diminished.
There exists a dichotomy in the communication strategies of fashion firms—some firms purposefully cloak information on the tastefulness of their products, whereas others openly flaunt their tasteful or “it” products. This divide in communication strategies cannot be explained by existing wealth signaling models of fashion.
Marketing managers and their companies are better served by spending less on building brand loyalty up front and maintaining a reserve for advertising during a post-crisis period. Further, ad spending after a crisis is more effective in building brand interest than before a crisis.
Solving Share Equations in Logit Models Using the LambertW Function
Review of Marketing Science, 2011
Though individual demand and supply equations can readily be expressed in logit models, closed-form solutions for equilibrium shares and prices are intractable due to the presence of products of polynomial and exponential terms. This hinders the employment of logit models in theoretical studies, and also makes it difficult to develop reduced-form expressions for share and price as a function of exogenous variables for use in empirical studies.
How should forward-looking managers plan advertising if they envision a product-harm crisis in the future? To address this question, Professor Olivier Rubel, Professor Prasad Naik and Professor Shuba Srinivasan propose a dynamic model of brand advertising in which, at each instant, a nonzero probability exists for the occurrence of a crisis event that damages the brand’s baseline sales and may enhance or erode marketing effectiveness when the crisis occurs. Because managers do not know when the crisis will occur, its random time of occurrence induces a stochastic control problem, which they solve analytically in closed form. More importantly, the envisioning of a possible crisis alters managers’ rate of time preference: anticipation enhances impatience.
Dynamic Marketing Budgeting for Platform Firms: Theory, Evidence and Application
Journal of Marketing Research, 2011
Few studies address the marketing budgeting problems of platform firms operating in two-sided markets with cross-market network effects, i.e., the demand from one customer group of the platform influences the demand from its other customer group. Yet such firms, e.g., media firms like newspapers whose customers are subscribers and advertisers, are prevalent in the marketplace and invest significantly in marketing.
Current models posit that awareness of advertising declines immediately and gradually once it is over, although anecdotal evidence from managers suggests that awareness stays constant for a while and then decays rapidly. This pattern arises because consumers remember advertisements for a finite time before they forget.
A spontaneous acceleration problem led Toyota to recall eight million cars globally and suspend sales of several models in November 2009 and in January. To make matters worse, in February Toyota suffered another blow when reports surfaced of faulty brakes on the Prius hybrid. The defects have battered the company’s reputation, resulting in huge losses and sinking consumer confidence.
Potential Design, Implementation, and Benefits of a Feebate Program for New Passenger Vehicles in California: Interim Statement of Research Findings
UC Davis Institute of Transportation Studies, 2010
Professor David Bunch and co-author David Greene of Oak Ridge National Laboratory completed a comprehensive study to assess the potential design, implementation, and benefits of a feebate program in California as well as possible stakeholder responses. This interim document summarizes the study’s key findings. A forthcoming project final report will include a more detailed presentation of results, and complete documentation on modeling and analysis tools, study methods, and limitations.
Professor Prasad Naik and Professor Kay Peters from the Center for Interactive Marketing and Media Management at the University of Münster, Germany, have won the 2010 Journal of Interactive Marketing Best Paper Award for their article, “A Hierarchical Marketing Communications Model of Online and Offline Media Synergies.”
The Big Pharma Dilemma: Develop New Products or Promote Existing Ones
Nature Reviews Drug Discovery, 2009
Big Pharma should take a closer look at their dosage of R&D spending on new drugs versus marketing existing ones, according to new research by Professor Prasad Naik. Pharmaceutical companies face the dilemma of how much to invest in developing new drugs and promoting existing ones.
Follow-on Development of CARBITS: a Response Model for the California Passenger Vehicle Market
State of California Air Resources Board, 2009
CARBITS is a market simulation model for the passenger vehicle market in California. Professor David S. Bunch developed CARBITS for the ARB during 2003-04 under a contract with the University of California, Davis. Its primary purpose is as a scenario analysis tool to evaluate market response under alternative regulation scenarios.
At a time when manufacturing and services are being outsourced, margins narrowed and the threat of commoditization a concern, organizations and their management need to foster what Assistant Professor Siobhán O´Mahony calls “design thinking” among their rank and file to maintain a competitive advantage.
Online reverse auctions generate real-time bidding data that could be used via appropriate statistical estimation to assist the corporate buyer’s procurement decision. To this end, Professor Prasad Naik and co-author Sandy Jap from Emory University develop a method, called BidAnalyzer, which estimates dynamic bidding models and selects the most appropriate of them.
Extracting Forward-Looking Information from Security Prices: A New Approach
The Accounting Review, 2008
This paper by Professors Prasad Naik, Chih-Ling Tsai and co-author Dan Weiss from Tel Aviv University proposes a new index to extract forward-looking information from security prices and infer market participants’ expectations of future earnings. The index, called market-adapted earnings (MAE), utilizes stock returns and fundamental accounting signals to estimate market expectations of future earnings at the firm level. MAE outperforms time-series models (e.g., random-walk) in predicting future earnings. Results demonstrate the usefulness of MAE for firms that have no analyst following.
This paper considers an infinite-horizon differential game played by two direct marketers. Each player controls the number of emails sent to potential customers at each moment in time. There is a cost associated to the messages sent, as well as a potential reward. The latter is assumed to depend on the state variable defined as the level of the representative consumer’s attention.
Companies spend hundreds of millions of dollars annually on advertising to build and maintain awareness for their brands in competitive markets. However, awareness formation models in the marketing literature ignore the role of competition. Consequently, we lack both the empirical knowledge and normative understanding of building brand awareness in dynamic oligopoly markets.
O’Mahony recently completed a paper titled, “Nexus Work: Managing Ambiguity in Market-Based Creative Projects,” coauthored with Elizabeth Long Lingo, research associate at the Curb Center for Art, Enterprise and Public Policy at Vanderbilt University. This collaborative work was recently recognized at the Fourth Annual Research Conference on “Creativity, Entrepreneurship and Organizations of the Future,” a Harvard Business School Centennial Colloquium on December 7-8, 2007. It was one of 10 papers out of 100 accepted into this elite colloquial series.
Perils of Using OLS to Estimate Multimedia Communications Effects
Journal of Advertising Research, 2007
Companies invest millions of dollars in various forms of marketing communications to impact customers’ awareness, attitudes, purchases, and, ultimately, profitability. An important question for marketers and shareholders alike is: what effects do marketing investments have on market performance?
Newspapers that invest more money in their newsrooms make more money. The media industry’s recent impulse to slash jobs to cut costs is not only ineffective, but can lead to more red ink, according to a study by Professor Prasad Naik and his research partners from the University of Missouri, Professor Murali K. Mantrala, Shrihari Sridhar and Professor Esther Thorson. Their study, “Uphill or Downhill? Locating your Firm on a Profit Function,” was published in the April 2007 issue of the Journal of Marketing.
Extending the Akaike Information Criterion for Mixture Regression Models
Journal of the American Statistical Association, 2007
In this paper, Professors Prasad Naik and Chih-Ling Tsai, with co-author Peide Shi from Nuclear Safety Solutions Ltd., examine the problem of jointly selecting the number of components and variables in finite mixture regression models.
Associate Professor Eyal Biyalogorsky and his co-authors, Professors William Boulding and Richard Staelin, both of Duke University’s Fuqua School of Business, received the 2006 Harold M. Maynard Award for their article, “Stuck in the Past: Why Managers Persists with New Product Failures,” published in the April 2006 issue of the Journal of Marketing. The journal’s Editorial Review Board selects the best article in a given year for its greatest contribution to marketing theory and thought.
The Effects of New Franchisor Partnering Strategies on Franchise System Size
Management Science, 2006
Many young firms use strategic actions to attract partners who help them increase the size of their operations quickly. This article examines the use of strategic actions to attract partners and increase system size in the context of franchising.
In Markov-switching regression models, Professors Prasad Naik, Chih-Ling Tsai and co-author Aaron Smith from the UC Davis Department of Agricultural and Resource Economics use Kullback–Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously.
Constrained Inverse Regression for Incorporating Prior Information
Journal of the American Statistical Association, 2005
Inverse regression methods facilitate dimension-reduction analyses of high-dimensional data by extracting a small number of factors that are linear combinations of the original predictor variables. But the estimated factors may not lend themselves readily to interpretation consistent with prior information.
Companies spend millions of dollars on advertising to boost a brand’s image and simultaneously spend millions of dollars on promotion that many believe calls attention to price and erodes brand equity. We believe this paradoxical situation exists because both advertising and promotion are necessary to compete effectively in dynamic markets. Consequently, brand managers need to account for interactions between marketing activities and interactions among competing brands.
Customer Equity: Making Marketing Strategy Financially Accountable
Journal of Systems Science and Systems Engineering, 2004
Traditionally, Return on Investment (ROI) models have been used to evaluate the financial expenditures required by the strategies as well as the financial returns gained by them. However in addition to requiring lengthy longitudinal data, these models also have the disadvantage of not evaluating the effect of the strategies on a firm’s customer equity. The dominance of customer-centered thinking over product-centered thinking calls for a shift from product-based strategies to customer-based strategies.
Isotonic Single-Index Model for High-Dimensional Database Marketing
Computational Statistics and Data Analysis, 2004
While database marketers collect vast amounts of customer transaction data, its utilization to improve marketing decisions presents problems. Marketers seek to extract relevant information from large databases by identifying significant variables and prospective customers. In small databases, they could calibrate logistic regression models via maximum-likelihood methods to determine significant variables and assess customer’s response probability.
Understanding the Impact of Synergy in Multimedia Communications
Journal of Marketing Research, 2003
Many advertisers adopt the integrated marketing communications perspective that emphasizes the importance of synergy in planning multimedia activities. However, the role of synergy in multimedia communications is not well understood.
Professor Prasad Naik was one of the top-five finalists for the prestigious 2008 William F. O’Dell Award, for his pioneering research on the role of synergy in integrating marketing communications. The American Marketing Association awards the honor for articles published in the Journal of Marketing Research over the last five years. The articles are judged by the Editorial Board as the “most significant, long-term contribution to marketing theory, methodology, and/or practice.”
in this paper, Professors Prasad Naik and Chih-Ling Tsai derive a new model selection criterion for single-index models, AIC, by minimizing the expected Kullback-Leibler distances between the true and candidate models.
The pro-posed criterion selects not only relevant variables but also the smoothing parameter for an unknown link function. Thus, it is a general selection criterion that provides a unifies approach to model selection across both parametric and nonparametric functions. Monte Carlo studies demonstrate that AIC performs satisfactorily in most situations.
Partial Least Squares Estimator for Single-index Models
Journal of the Royal Statistical Society, 2000
The partial least squares (PLS) approach first constructs new explanatory variables, known as factors (or components), which are linear combinations of available predictor variables. A small subset of these factors is then chosen and retained for prediction.
A New Dimension Reduction Approach for Data-Rich Marketing Environments: Sliced Inverse Regression
Journal of Marketing Research, 2000
In data-rich marketing environments (e.g., direct marketing or new product design), managers face an ever-growing need to reduce the number of variables effectively. To accomplish this goal, Professors Prasad Naik and Chih-Ling Tsai and co-author Michael Hagerty introduce a new method called sliced inverse regression (SIR), which finds factors by taking into account the information contained in both the dependent and independent variables.
In this paper, Professor David Bunch and co-author Herb Johnson of the University of California, Riverside derive an expression for the critical stock price for the American put. The authors start by expressing the put price as an integral involving first-passage probabilities. This approach yields intuition for Merton’s result for the perpetual put. The authors then consider the finite-lived case.
Controlling Measurement Errors in Models of Advertising Competition
Journal of Marketing Research, 2000
Commercial market research firms provide information on advertising variables of interest, such as brand awareness or gross rating points, that are likely to contain measurement errors. This unreliability of measured variables induces bias in the estimated parameters of dynamic models of advertising. Consequently, advertisers either under- or overspend on advertising to maintain a desired level of brand awareness.
A key task of advertising media planners is to determine the best media schedule of advertising exposures for a certain budget. Conceptually, the planner could choose to do continuous advertising (i.e., schedule ad exposures evenly over all weeks) or follow a strategy of pulsing (i.e., advertise in some weeks of the year and not at other times).