A Method for Asynchronous Time Series Analysis with Marketing Applications

References

• Aaker D, Stayman D (1990) Measuring audience perceptions of commercials and relating them to ad impact. J. Advertising Res. 30(4):7–18.Crossref, Google Scholar
• Almon S (1965) The distributed lag between capital appropriations and expenditures. Econometrica 33(1):178–196.Crossref, Google Scholar
• Anderson BD, Moore JB (1979) Optimal Filtering (Prentice–Hall, Hoboken, NJ).Google Scholar
• Ataman MB, Mela CF, van Heerde HJ (2008) Building brands. Marketing Sci. 27(6):1036–1054.Link, Google Scholar
• Baumgartner H, Sujan M, Padgett D (1997) Patterns of affective reactions to advertisements: The integration of moment-to-moment responses into overall judgments. J. Marketing Res. 34(2):219–232.Crossref, Google Scholar
• Bedrick EJ, Tsai C-L (1994) Model selection for multivariate regression in small samples. Biometrics 50(1):226–231.Crossref, Google Scholar
• Bernanke BS, Boivin J, Eliasz P (2005) Measuring the effects of monetary policy: A factor-augmented vector autoregressive (FAVAR) approach. Quart. J. Econom. 120(1):387–422.Google Scholar
• Biel AL, Bridgewater C (1990) Attributes of likable television commercials. J. Advertising Res. 30(3):38–44.Crossref, Google Scholar
• Biyalogorsky E, Naik PA (2003) Clicks and mortar: The effect of online activities on offline sales. Marketing Lett. 14(1):21–32. Crossref, Google Scholar
• Bretous M (2022) How brands are investing in video marketing on a budget. Accessed September 9, 2020, https://blog.hubspot.com/marketing/video-on-budget.Google Scholar
• Brockwell PJ, Davis RA (1996) Introduction to Time Series and Forecasting (Springer, New York).Crossref, Google Scholar
• Bruce NI, Peters K, Naik PA (2012) Discovering how advertising grows sales and builds brands. J. Marketing Res. 49(6):793–806.Crossref, Google Scholar
• Clarke DG (1976) Econometric measurement of the duration of advertising effect on sales. J. Marketing Res. 13(4):345–357.Crossref, Google Scholar
• Danaher PJ (2023) Optimal microtargeting of advertising. J. Marketing Res. 60(3):564–584.Crossref, Google Scholar
• Durbin J, Koopman SJ (2001) Time Series Analysis by State Space Methods, Oxford Statistical Science Series (London).Google Scholar
• Elpers J, Mukherjee A, Hoyer WD (2004) Humor in television advertising: A moment-to-moment analysis. J. Consumer Res. 31(3):592–598.Crossref, Google Scholar
• Elpers J, Wedel M, Pieters RGM (2003) Why do consumers stop viewing television commercials? Two experiments on the influence of moment-to-moment entertainment and information value. J. Marketing Res. 40(4):437–453.Crossref, Google Scholar
• Fuh C-D (2006) Efficient likelihood estimation in state space models. Ann. Statist. 34(4):2026–2068.Crossref, Google Scholar
• Ghysels E, Sinko A, Valkanov R (2007) MIDAS regressions: Further results and new directions. Econometric Rev. 26(1):53–90.Crossref, Google Scholar
• Giannone D, Reichlin L, Small D (2008) Nowcasting: The real-time informational content of macroeconomic data. J. Monetary Econom. 55(4):665–676.Crossref, Google Scholar
• Goldfarb A, Tucker CE (2015) Standardization and the effectiveness of online advertising. Management Sci. 61(11):2707–2719.Link, Google Scholar
• Hamilton JD (1994) Time Series Analysis (Princeton University Press, Princeton, NJ). Crossref, Google Scholar
• Harvey AC (2001) Forecasting, Structural Time Series Models and the Kalman Filter (Cambridge University Press, New York).Google Scholar
• Holbrook M, Batra R (1987) Assessing the role of emotions as mediators of consumer responses to advertising. J. Consumer Res. 14(3):404–420.Crossref, Google Scholar
• Hui S, Meyvis T, Assael H (2014) Analyzing moment-to-moment data using a Bayesian functional linear model: Application to TV show pilot testing. Marketing Sci. 33(2):222–240.Link, Google Scholar
• Hwang M, Thomadsen R (2016) How point-of-sale marketing mix impacts national-brand purchase shares. Management Sci. 62(2):571–590.Link, Google Scholar
• Jazwinski AH (1970) Stochastic Processes and Filtering Theory (Academic Press, Pittsburgh).Google Scholar
• Jedidi K, Mela CF, Gupta S (1999) Managing advertising and promotion for long-run profitability. Marketing Sci. 18(1):1–22.Link, Google Scholar
• Jensen JL, Petersen NV (1999) Asymptotic normality of the maximum likelihood estimator in state space models. Ann. Statist. 27(2):514–535.Crossref, Google Scholar
• Kim M, Bradlow ET, Iyengar R (2022) Selecting data granularity and model specification using the scaled power likelihood with multiple weights. Marketing Sci. 41(4):848–866.Link, Google Scholar
• Kolsarici C, Vakratsas D, Naik PA (2020) The anatomy of the advertising budget decision: How analytics and heuristics drive sales performance. J. Marketing Res. 57(3):468–488.Crossref, Google Scholar
• Koop G, Korobilis D (2010) Bayesian multivariate time series methods for empirical macroeconomics. Foundations Trends Econometrics 3(4):267–358.Crossref, Google Scholar
• Lebow S (2022) The MVP of video advertising in the US. Accessed September 9, 2022, https://www.insiderintelligence.com/content/mvp-video-advertising/.Google Scholar
• Lee D, Hosanagar K, Nair HS (2018) Advertising content and consumer engagement on social media: Evidence from Facebook. Management Sci. 64(11):5105–5131.Link, Google Scholar
• Leone RP (1995) Generalizing what is known about temporal aggregation and advertising carryover. Marketing Sci. 14(3):141–150.Link, Google Scholar
• Liu X, Shi S, Teixeira T, Wedel M (2018) Video content marketing: The making of clips. J. Marketing 82(4):86–101.Crossref, Google Scholar
• Loewenstein J, Raghunathan R, Heath C (2011) The repetition-break plot structure makes effective television advertisements. J. Marketing 75(5):105–119.Crossref, Google Scholar
• Lütkepohl H (2005) New Introduction to Multiple Time Series Analysis (Springer, Berlin).Crossref, Google Scholar
• Madrigal R, Bee C (2005) Suspense as an experience of mixed emotions: Feelings of hope and fear while watching suspenseful commercials. Adv. Consumer Res. 32:561–567.Google Scholar
• Mariano RS, Murasawa Y (2003) A new coincident index of business cycles based on monthly and quarterly series. J. Appl. Econometrics 18(4):427–443.Crossref, Google Scholar
• Meinhold RJ, Singpurwalla ND (1983) Understanding the Kalman filter. Amer. Statist. 37(2):123–127.Crossref, Google Scholar
• Mittnik S, Zadrozny P (2004) Forecasting quarterly German GDP at monthly intervals using monthly IFO business conditions data. CESifo Working Paper No. 1203, Munich.Google Scholar
• Moldovan SE (1984) Copy factors related to persuasion scores. J. Advertising Res. 24(6):16–22.Crossref, Google Scholar
• Naik PA (2015) Marketing dynamics: A primer on estimation and control. Foundations Trends Marketing 9(3):175–266.Crossref, Google Scholar
• Naik PA, Raman K (2003) Understanding the impact of synergy in multimedia communications. J. Marketing Res. 40(4):375–388.Crossref, Google Scholar
• Naik PA, Tsai C-L (2000) Controlling measurement errors in models of advertising competition. J. Marketing Res. 37(1):113–124.Crossref, Google Scholar
• Naik PA, Mantrala MK, Sawyer AG (1998) Planning media schedules in the presence of dynamic advertising quality. Marketing Sci. 17(3):214–235.Link, Google Scholar
• Naik PA, Prasad A, Sethi S (2008) Building brand awareness in dynamic oligopoly markets. Management Sci. 54(1):129–138.Link, Google Scholar
• Pauwels K, Currim I, Dekimpe MG, Ghysels E, Hanssens DM, Mizik N, Naik PA (2004) Modeling marketing dynamics by time series econometrics. Marketing Lett. 15(4):167–183.Crossref, Google Scholar
• Pieters R, Warlop L, Wedel M (2002) Breaking through the clutter: Benefits of advertisement originality and familiarity for brand attention and memory. Management Sci. 48(6):765–781.Link, Google Scholar
• Pieters R, Wedel M, Zhang J (2007) Optimal feature advertising design under competitive clutter. Management Sci. 53(11):1815–1828.Link, Google Scholar
• Raudenbush SW, Bryk AS (2002) Hierarchical Linear Models: Applications and Data Analysis Methods, 2nd ed. (Sage, Thousand Oaks, CA).Google Scholar
• Runge J, Patter H, Skokan I (2023) A new gold standard for digital ad measurement? Harvard Business Review Online (March 24), https://hbr.org/2023/03/a-new-gold-standard-for-digital-ad-measurement.Google Scholar
• Schlinger MJ (1979) A profile of responses to commercials. J. Advertising Res. 19(2):37–46.Crossref, Google Scholar
• Schweidel DA, Knox G (2013) Incorporating direct marketing activity into latent attrition models. Marketing Sci. 32(3):471–487.Link, Google Scholar
• Shehu E, Bijmolt THA, Clement M (2016) Effects of likeability dynamics on consumers’ intention to share online video advertisements. J. Interactive Marketing 35(1):27–43.Crossref, Google Scholar
• Shumway RH, Stoffer DS (1982) An approach to time series smoothing and forecasting using the EM algorithm. J. Time Ser. Anal. (Oxford) 3(4):253–264.Crossref, Google Scholar
• Shumway RH, Stoffer DS (2016) Time Series Analysis and Its Applications: With R Examples, 4th ed. (Springer, New York).Google Scholar
• Smit EG, Van Meurs LV, Neijens PC (2006) Effects of advertising likeability: A 10-year perspective. J. Advertising Res. 46(1):73–83.Crossref, Google Scholar
• Steenkamp JBEM, Baumgartner H, van der Wulp E (1996) Arousal potential, arousal, stimulus attractiveness, and the moderating role of the need for stimulation. Internat. J. Res. Marketing 13(4):319–329.Crossref, Google Scholar
• Teixeira T, Picard R, Kaliouby R (2014) Why, when, and how much to entertain consumers in advertisements? A web-based facial tracking field study. Marketing Sci. 33(6):809–827.Link, Google Scholar
• Teixeira T, Wedel M, Pieters R (2012) Emotion-induced engagement in internet video advertisements. J. Marketing Res. 49(2):144–159.Crossref, Google Scholar
• Valenti A, Yildirim G, Vanhuele M, Srinivasan S, Pauwels K (2023) Advertising’s sequence of effects on consumer mindset and sales: A comparison across brands and product categories. Internat. J. Res. Marketing 40(2):435–454.Crossref, Google Scholar
• Wei WS (1978) The effect of temporal aggregation on parameter estimation in distributed lag model. J. Econometrics 8(2):237–246.Crossref, Google Scholar
• Wells W, Leavitt C, McConville M (1971) A reaction profile for TV commercials. J. Advertising Res. 11(6):11–18.Crossref, Google Scholar
• Zadrozny P (1990) Estimating a multivariate ARMA model with mixed frequency data: An application to forecasting US GNP at monthly intervals. Working paper, Center for Economic Studies, U.S. Bureau of the Census, Washington, DC.Google Scholar
• Zantedeschi D, Feit EM, Bradlow ET (2017) Measuring multichannel advertising response. Management Sci. 63(8):2706–2728.Link, Google Scholar
• Zinkham GM, Fornell C (1985) A test of two consumer response scales in advertising. J. Marketing Res. 22(4):447–452.Crossref, Google Scholar