For Internet retailers, demand propagation varies not only through time but also over space. The authors develop a Bayesian spatiotemporal model to study two imitation effects in the evolution of demand at an Internet retailer. Building on previous literature, the authors allow imitation behavior to be reflected both in geographic proximity and in demographic similarity. As these imitation effects can be time varying, the authors specify their dynamics using a “polynomial smoother” embedded within the Bayesian framework. They apply the model to new buyers at Netgrocer. com and calibrate it on 45 months of data that span all 1459 zip codes in Pennsylvania. The authors find that the proximity effect is especially strong in the early phases of demand evolution, whereas the similarity effect becomes more important with time. Over time, new buyers are increasingly likely to emerge from new zip codes beyond the “core set” of zip codes that produce the early new buyers, and spatial concentration declines. The authors explore the managerial implications stemming from these findings through a hypothetical “seeding” experiment. They also discuss other implications for Internet retailing practice.
AgrawalAjay, KapurDevesh, and McHaleJohn, (2008), “How Do Spatial and Social Proximity Influence Knowledge Flows? Evidence from Patent Data,”Journal of Urban Economics, 64(2), 258–69.
2.
AgrestiAlan, (2002), Categorical Data Analysis.New York: John Wiley & Sons.
3.
AlbuquerquePaulo, BronnenbergBart J., and CorbettCharles J., (2007), “A Spatiotemporal Analysis of the Global Diffusion of ISO 9000 and ISO 14000 Certification,”Management Science, 53(3), 451–68.
4.
AndersonChris, (2006), The Long Tail: Why the Future of Business Is Selling Less of More.New York: Hyperion.
5.
AngersJean-Francois, and DelampadyMohan, (1992), “Hierarchical Bayesian Curve Fitting and Smoothing,”The Canadian Journal of Statistics, 20(1), 35–49.
6.
AnselinLuc, (1988), Spatial Econometrics: Methods and Models.Boston: Kluwer.
7.
AveryJill, SteenburghThomas J., DeightonJohn, and CaravellaMary, (2008), “Adding Bricks to Clicks: The Effects of Store Openings on Sales through Direct Channels,” working paper, Harvard Business School, Harvard University.
8.
BalasubramanianSridhar, (1998), “Mail Versus Mall: A Strategic Analysis of Competition Between Direct Marketers and Conventional Retailers,”Marketing Science, 17(3), 181–95.
9.
BassFrank, (1969), “A New Product Growth Model for Consumer Durables,”Management Science, 15(5), 215–27.
10.
BassFrank, BruceNorris, MajundarSumit, and MurthiB.P.S., (2007), “Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising–Sales Relationship,”Marketing Science, 26(2), 179–95.
11.
BellDavid R., and SongSangyoung, (2007), “Neighborhood Effects and Trial on the Internet: Evidence from Online Grocery Retailing,”Quantitative Marketing and Economics, 5(4), 361–400.
12.
BronnenbergBart J., and MelaCarl F., (2004), “Market Roll-Out and Retailer Adoption of New Brands,”Marketing Science, 23(4), 500–518.
13.
BrynjolfssonEric, HuYu (Jeffrey), and RahmanMohammad S., (2008), “Battle of the Retail Channels: How Product Selection and Geography Drive Cross-Channel Competition,” working paper, Sloan School of Management, Massachusetts Institute of Technology.
14.
BrynjolfssonEric, HuYu (Jeffrey), and SimesterDuncan, (2006), “Goodbye Pareto Principle, Hello Long Tail,” working paper, Sloan School of Management, Massachusetts Institute of Technology.
15.
ChibSiddhartha, (1995), “Marginal Likelihood from the Gibbs Output,”Journal of the American Statistical Association, 90(432), 1313–21.
16.
ChibSiddhartha, and JeliazkovIvan, (2001), “Marginal Likelihood From the Metropolis-Hastings Output,”Journal of the American Statistical Association, 96(453), 270–81.
17.
ClaudeBesner, (2002), “A Spatial Autoregressive Specification with a Comparable Sales Weighting Scheme,”Journal of Real Estate Research, 24(2), 193–211.
18.
ConleyTimothy G., and TopaGiorgio, (2002), “Socio-Economic Distance and Spatial Patterns in Unemployment,”Journal of Econometrics, 17(4), 303–327.
19.
CressieNoel, (1993), Statistics for Spatial Data.New York: John Wiley & Sons.
20.
FischerClaude, S., (1978), “Urban-to-Rural Diffusion of Opinions in Contemporary America,”American Journal of Sociology, 84(1), 151–59.
21.
FormanChris, GhoseAnindya, and GoldfarbAvi, (2009), “Competition Between Local and Electronic Markets: How the Benefit of Buying Online Depends on Where You Live,”Management Science, 55(1), 47–57.
22.
FormanChris, GhoseAnindya, and WiesenfeldBatia, (2008), “Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets,”Information Systems Research, 19(3), 291–313.
23.
GelmanAndrew, CarlinJohn B., SternHal S., and RubinDonald B., (2003), Bayesian Data Analysis, 2d ed.New York: Chapman & Hall.
24.
GetisArthur, and Keith OrdJ., (1992), “The Analysis of Spatial Association by Use of Distance Statistics,”Geographical Analysis, 24(3), 189–206.
25.
GodesDavid, and MayzlinDina, (2004), “Using Online Conversations to Study Word-of-Mouth Communication,”Marketing Science, 23(4), 545–60.
26.
GodesDavid, and MayzlinDina, (2009), “Firm-Created Word-of-Mouth Communication: Evidence from a Field Test,”Marketing Science, 28(4), 721–39.
27.
GoolsbeeAustan, and KlenowPeter J., (2002), “Evidence of Learning and Network Externalities in the Diffusion of Home Computers,”Journal of Law and Economics, 45(2), 317–42.
28.
HastieTrevor, TibshiraniRobert, and FriedmanJerome, (2001), The Elements of Statistical Learning.New York: Springer.
29.
HauserJohn, TellisGerard J., and GriffinAbbie, (2006), “Research on Innovation: A Review and Agenda for Marketing Science,”Marketing Science, 25(6), 687–717.
30.
HowardPhilip E., RaineLee, and JonesSteve, (2001), “Access, Civic Involvement, and Social Interaction,”American Behavioral Scientist, 45(3), 382–404.
31.
HuffDavid, L., (1964), “Defining and Estimating a Trade Area,”Journal of Marketing, 28(July), 34–38.
32.
JankWolfgang, and KannanP.K., (2005), “Understanding Geographic Markets of Online Firms Using Spatial Models of Customer Choice,”Marketing Science, 24(4), 623–34.
33.
KalyanamKirthi, and ShivelyThomas S., (1998), “Estimating Irregular Pricing Effects: A Stochastic Spline Regression Approach,”Journal of Marketing Research, 35(February), 16–29.
34.
KatzJames E., RiceRonald E., and AspdenPhilip, (2001), “The Internet, 1995–2000,”American Behavioral Scientist, 45(3), 405–419.
35.
Knorr-HeldLeonhard, and BesagJulian, (1998), “Modeling Risk from a Disease in Time and Space,”Statistics in Medicine, 17(18), 2045–2060.
36.
LeSageJ.P., and PaceR.K., (2005), “Matrix Exponential Spatial Specification,”Journal of Econometrics, 140(1), 190–214.
37.
LibaiBarak, MullerEitan, and PeresRenana, (2005), “The Role of Seeding in Multi-Market Entry,”International Journal of Research in Marketing, 22(4), 375–93.
ManchandaPuneet, XieYing, and YounNara, (2008), “The Role of Targeted Communication and Contagion in Product Adoption,”Marketing Science, 27(6), 961–76.
40.
ManskiCharles, F., (1993), “Identification of Endogenous Social Effects: The Reflection Problem,”Review of Economic Studies, 60(3), 531–42.
41.
ManskiCharles, F., (2000), “Economic Analysis of Social Interactions,”Journal of Economic Perspectives, 14(3), 115–36.
42.
NewtonMichael A., and RafteryAdrian E., (1994), “Approximate Bayesian Inference by the Weighted Likelihood Bootstrap,”Journal of Royal Statistical Society: Series B, 56(1), 41–42.
43.
PauwelsKoen, and NeslinScott A., (2008), “Building Bricks and Mortar: The Impact of Opening Physical Stores in a Multichannel Environment,” MSI Working Paper No. 08–102.
44.
Rabe-HeskethSophia, and SkrondalAnders, (2005), Multilevel and Longitudinal Modeling Using Stata.College Station, TX: Statacorp LP.
45.
RosenblatTanya S., and MobiusMarkus M., (2004), “Getting Closer or Drifting Apart?”Quarterly Journal of Economics, 119(3), 971–1009.
46.
RossSheldon, M., (1996), Stochastic Processes, 2d ed.New York: John Wiley & Sons.
47.
RossiPeter E., and AllenbyGreg M., (2003), “Bayesian Statistics and Marketing,”Marketing Science, 22(3), 304–328.
48.
Van AlstyneMarshall, and BrynjolfssonErik, (2005), “Global Village or Cyber-Balkans? Modeling and Measuring the Integration of Electronic Communities,”Management Science, 51(6), 851–68.
49.
Van den BulteChristophe, and JoshiYogesh V., (2007), “New Product Diffusion with Influentials and Imitators,”Marketing Science, 26(3), 400–421.
50.
Van den BulteChristophe, and LilienGary L., (1997), “Bias and Systematic Change in the Parameter Estimates of Macro-Level Diffusion Models,”Marketing Science, 16(4), 338–53.
51.
WahbaGrace, (1978), “Improper Priors, Spline Smoothing and the Problem of Guarding Against Model Errors in Regression,”Journal of the Royal Statistical Society: Series B, 40(3), 364–72.
52.
WaldfogelJoel, (2007), The Tyranny of the Market.Cambridge, MA: Harvard University Press.
53.
WandMatt, P., (2003), “Smoothing and Mixed Models,”Computational Statistics, 18(2), 223–49.
54.
WedelMichel, and ZhangJie, (2004), “Analyzing Brand Competition Across Subcategories,”Journal of Marketing Research, 41(November), 448–56.
55.
WikleChristopher K., and HootenMevin B., (2006), “Hierarchical Bayesian Spatio-Temporal Models for Population Spread,” in Applications of Computational Statistics in the Environmental Sciences: Hierarchical Bayes and MCMC Methods, ClarkJ.S., and GelfandA., eds. Oxford: Oxford University Press, 144–69.
56.
YangSha, and AllenbyGreg M., (2003), “Modeling Interdependent Consumer Preferences,”Journal of Marketing Research, 40(August), 282–94.
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