@article{moon_azizi_2013, title={Finding donors by relationship fundraising}, volume={27}, number={2}, journal={Journal of Interactive Marketing}, author={Moon, S. and Azizi, K.}, year={2013}, pages={112–129} }
 @article{moon_2011, title={An empirical investigation of dual network effects in innovation project development}, volume={25}, number={4}, journal={Journal of Interactive Marketing}, author={Moon, S.}, year={2011}, pages={215–225} }
 @article{moon_bergey_iacobucci_2010, title={Dynamic Effects Among Movie Ratings, Movie Revenues, and Viewer Satisfaction}, volume={74}, ISSN={["1547-7185"]}, DOI={10.1509/jmkg.74.1.108}, abstractNote={ This research investigates how movie ratings from professional critics, amateur communities, and viewers themselves influence key movie performance measures (i.e., movie revenues and new movie ratings). Using movie-level data, the authors find that high early movie revenues enhance subsequent movie ratings. They also find that high advertising spending on movies supported by high ratings maximizes the movie's revenues. Furthermore, they empirically show that sequel movies tend to reap more revenues but receive lower ratings than originals. Using individual viewer–level data, this research highlights how viewers’ own viewing and rating histories and movie communities’ collective opinions explain viewer satisfaction. The authors find that various aspects of these ratings explain viewers’ new movie ratings as a measure of viewer satisfaction, after controlling for movie characteristics. Furthermore, they find that viewers’ movie experiences can cause them to become more critical in ratings over time. Finally, they find a U-shaped relationship between viewers’ genre preferences and genre-specific movie ratings for heavy viewers. }, number={1}, journal={JOURNAL OF MARKETING}, author={Moon, Sangkil and Bergey, Paul K. and Iacobucci, Dawn}, year={2010}, month={Jan}, pages={108–121} }
 @article{moon_voss_2009, title={How do price range shoppers differ from reference price point shoppers?}, volume={62}, ISSN={["0148-2963"]}, DOI={10.1016/j.jbusres.2008.01.017}, abstractNote={Existing research demonstrates that reference price models can explain a significant amount of the variation in customers' price perceptions and purchase behaviors. This study extends the reference price literature by introducing the price range model, which proposes that price judgments are based on a comparison of the market price to the entire range of currently available prices. Our results demonstrate that the fit of a structural heterogeneity finite mixture model improves when the price range model is included along with internal and external reference price models and that the price range model explains a substantial proportion of customers' purchase histories in the toilet tissue category. Profile analysis indicates that internal reference price shoppers switch brands much less frequently than the other two segments and respond to feature promotions for their preferred brand(s). External reference price shoppers have an intermediate level of brand preference and respond significantly less than the other two segments to feature and display promotions. Price range shoppers have the lowest brand loyalty and respond most strongly to both feature and display promotions.}, number={1}, journal={JOURNAL OF BUSINESS RESEARCH}, author={Moon, Sangkil and Voss, Glenn}, year={2009}, month={Jan}, pages={31–38} }
 @article{kamakura_moon_2009, title={Quality-adjusted price comparison of non-homogeneous products across Internet retailers}, volume={26}, ISSN={["1873-8001"]}, DOI={10.1016/j.ijresmar.2009.03.004}, abstractNote={This study compares prices offered by multiple Internet retailers. This task is challenging because e-tailers cannot present their entire assortments to each consumer. Therefore, the quality of the product assortments presented by different e-tailers to each consumer is not directly comparable on an item-by-item basis, resulting in non-homogeneous offerings across retailers. We further consider the interaction between retailers (product information presentation format) and consumers (product information search strategies), which makes price comparisons among the retailers even more non-homogeneous. To grapple with this quality-adjusted price comparison problem for non-homogeneous products, we use a stochastic-frontier hedonic-price regression model to find the “lowest” theoretical price for a product given its characteristics. We then assess the price efficiency of the product as the ratio between this lowest price and the offered market price. This framework allows for the comparison of retailers in their ability to offer the “best deals” even when their actual assortments are not directly comparable in quality. Moreover, this framework provides Internet retailers with a relative measure of price efficiency. This helps them understand when and where they offer competitive prices to consumers. We illustrate our approach empirically in a comparison of price efficiency among three major Internet travel agents on a sample of posted itineraries and airfares. Furthermore, we demonstrate that the price efficiency of an Internet travel agent depends on the format of its website and on consumers' search strategies.}, number={3}, journal={INTERNATIONAL JOURNAL OF RESEARCH IN MARKETING}, author={Kamakura, Wagner A. and Moon, Sangkil}, year={2009}, month={Sep}, pages={189–196} }
 @article{moon_russell_2008, title={Predicting product purchase from inferred customer similarity: An autologistic model approach}, volume={54}, ISSN={["1526-5501"]}, DOI={10.1287/mnsc.1070.0760}, abstractNote={ Product recommendation models are key tools in customer relationship management (CRM). This study develops a product recommendation model based on the principle that customer preference similarity stemming from prior purchase behavior is a key element in predicting current product purchase. The proposed recommendation model is dependent on two complementary methodologies: joint space mapping (placing customers and products on the same psychological map) and spatial choice modeling (allowing observed choices to be correlated across customers). Using a joint space map based on past purchase behavior, a predictive model is calibrated in which the probability of product purchase depends on the customer's relative distance to other customers on the map. An empirical study demonstrates that the proposed approach provides excellent forecasts relative to benchmark models for a customer database provided by an insurance firm. }, number={1}, journal={MANAGEMENT SCIENCE}, author={Moon, Sangkil and Russell, Gary J.}, year={2008}, month={Jan}, pages={71–82} }
 @article{moon_kamakura_ledolter_2007, title={Estimating promotion response when competitive promotions are unobservable}, volume={44}, ISSN={["1547-7193"]}, DOI={10.1509/jmkr.44.3.503}, abstractNote={ This study addresses a problem commonly encountered by marketers who attempt to assess the impact of their sales promotions—namely, the lack of data on competitive marketing activity. In most industries, competing firms may have competitive sales data from syndicated services or trade organizations, but they seldom have access to data on competitive promotions at the customer level. Promotion response models in the literature either have ignored competitive promotions, focusing instead on the focal firm's promotions and sales response, or have considered the ideal situation in which the analyst has access to full information about each firm's sales and promotion activity. The authors propose a random coefficients hidden Markov promotion response model, which takes the competitor's unobserved promotion level as a latent variable driven by a Markov process to be estimated simultaneously with the promotion response model. This enables the authors to estimate cross-promotion effects by imputing the level of competitive promotions. The authors test the proposed model on synthetic data through a Monte Carlo experiment. Then, they apply and test the model to actual prescription and sampling data from two main competing pharmaceutical firms in the same therapeutic category. The two tests show that compared with several benchmark models, the proposed random coefficients hidden Markov model successfully imputes unobserved competitive promotions and, accordingly, reduces biases in the own- and cross-promotion parameters. Furthermore, the proposed model provides better predictive validity than the benchmark models. }, number={3}, journal={JOURNAL OF MARKETING RESEARCH}, author={Moon, Sangkil and Kamakura, Wagner A. and Ledolter, Johannes}, year={2007}, month={Aug}, pages={503–515} }
 @article{moon_russell_duvvuri_2006, title={Profiling the reference price consumer}, volume={82}, ISSN={["0022-4359"]}, DOI={10.1016/j.jretai.2005.11.006}, abstractNote={Researchers in marketing have devoted considerable attention to understanding how price impacts the purchase decision. Some individuals, termed memory-based reference price (MBR) consumers, take into account price expectations developed from past purchase behavior when making a current choice. Other individuals, termed stimulus-based reference price (SBR) consumers, make choices by constructing a reference point from the currently observed distribution of prices. Using a latent class model of structural heterogeneity applied to purchase histories from the toilet tissue category, we classify households in terms of the pricing mechanism used in buying decisions. We find strong evidence that memory-based (internal) reference price consumers are more price sensitive than other consumers. Moreover, we find that variables associated with the accessibility of price information are predictive of consumer use of memory-based reference prices. Managerial implications of these results are discussed.}, number={1}, journal={JOURNAL OF RETAILING}, author={Moon, S and Russell, GJ and Duvvuri, SD}, year={2006}, pages={1–11} }