Synergistic, Antagonistic, and Asymmetric Media Interactions

REFERENCES

• Ackoff, Russell L., and James R. Emshoff (1975), “Advertising Research at Anheuser-Busch, Inc. (1963–68),” Sloan Management Review, 16 (2), 1–15.
   Google Scholar
• AdAge (2015), “Top 15 Advertising Campaigns of the 21st Century,” http://adage.com/lp/top15/.
   Google Scholar
• Assael, Henry (2011), “From Silos to Synergy,” Journal of Advertising Research, 51 (1), 42–58.
   Web of Science ®Google Scholar
• Bass, Frank M., Norris Bruce, Sumit Majumdar, and B.P.S. Murthi (2007), “Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising-Sales Relationship,” Marketing Science, 26 (2), 179–95.
   Web of Science ®Google Scholar
• Batra, Rajeev, and Kevin Lane Keller (2016), “Integrating Marketing Communications: New Findings, New Lessons, and New Ideas,” Journal of Marketing, 80 (6), 122–45.
   Web of Science ®Google Scholar
• Belch, George E. (1982), “The Effects of Television Commercial Repetition on Cognitive Response and Message Acceptance,” Journal of Consumer Research, 9 (1), 56–65.
   Web of Science ®Google Scholar
• Cacioppo, John T., and Richard E. Petty (1979), “Effects of Message Repetition and Position on Cognitive Response, Recall, and Rersuasion,” Journal of personality and Social Psychology, 37 (1), 97–109.
   Web of Science ®Google Scholar
• Chang, Yuhmiin, and Esther Thorson (2004), “Television and Web Advertising Synergies,” Journal of Advertising, 33 (2), 75–84.
   Web of Science ®Google Scholar
• Chib, Siddhartha, Edward Greenberg, and Ivan Jeliazkov (2009), “Estimation of Semiparametric Models in the Presence of Endogeneity and Sample Selection,” Journal of Computational and Graphical Statistics, 18 (2), 321–48.
   Web of Science ®Google Scholar
• Corning, Peter A (1998), “‘The Synergism Hypothesis’: On the Concept of Synergy and Its Role in the Evolution of Complex Systems,” Journal of Social and Evolutionary Systems, 21 (2), 133–72.
   Google Scholar
• Danaher, Peter J., André Bonfrer, and Sanjay Dhar (2008), “The Effect of Competitive Advertising Interference on Sales for Packaged Goods,” Journal of Marketing Research, 45 (2), 211–25.
   Web of Science ®Google Scholar
• Danaher, Peter J., and Tracey S. Dagger (2013), “Comparing the Relative Effectiveness of Advertising Channels: A Case Study of a Multimedia Blitz Campaign,” Journal of Marketing Research, 50 (4), 517–34.
   Web of Science ®Google Scholar
• De Veaux, Richard D., and Lyle H. Ungar (1994), “Multicollinearity: A Tale of Two Nonparametric Regressions,” in Selecting Models from Data: Artificial Intelligence and Statistics IV, P. Cheeseman and R.W. Oldford, eds., New York: Springer-Verlag, 393–402.
   Google Scholar
• Dhar, Tirtha, and Charles B. Weinberg (2015), “Measurement of Interactions in Non-Linear Marketing Models: The Effect of Critics’ Ratings and Consumer Sentiment on Movie Demand,” International Journal of Research in Marketing, 33 (2), 392–408.
   Web of Science ®Google Scholar
• Dijkstra, Majorie, Heidi E.J.J.M. Buijtels, and W. Fred van Raaij (2005), “Separate and Joint Effects of Medium Type on Consumer Responses: A Comparison of Television, Print, and the Internet,” Journal of Business Research, 58 (3), 377–86.
   Web of Science ®Google Scholar
• Dubé, Jean-Pierre, Günter J. Hitsch, and Puneet Manchanda (2005), “An Empirical Model of Advertising Dynamics,” Quantitative Marketing and Economics, 3 (2), 107–44.
   Web of Science ®Google Scholar
• Duncan, Thomas R. (2002), IMC: Using Advertising and Promotion to Build Brands, Boston: McGraw-Hill.
   Google Scholar
• Eastlack, Joseph O., and Ambar G. Rao (1986), “Modeling Response to Advertising and Pricing Changes for ‘V-8’ Cocktail Vegetable Juice,” Marketing Science, 5 (3), 245–59.
   Google Scholar
• Eastlack, Joseph O., and Ambar G. Rao (1989), “Advertising Experiments at the Campbell Soup Company,” Marketing Science, 8 (1), 57–71.
   Web of Science ®Google Scholar
• Edell, Julie A., and Kevin Lane Keller (1989), “The Information Processing of Coordinated Media Campaigns,” Journal of Marketing Research, 26 (2), 149.
   Web of Science ®Google Scholar
• Ehrenberg-Bass Institute for Marketing Science (2012), “Planning for Synergy: Harnessing the Power of Multi-Platform Media,” https://www.marketingscience.info/wp-content/uploads/2016/01/Institute-and-CNCB-Synergy-White_Paper.pdf.
   Google Scholar
• Enoch, Glenn, and Kelly Johnson (2010), “Cracking the Cross-Media Code,” Journal of Advertising Research, 50 (2), 125.
   Web of Science ®Google Scholar
• Fischer, Marc, Sönke Albers, Nils Wagner, and Monika Frie (2011), “Practice Prize Winner-Dynamic Marketing Budget Allocation Across Countries, Products, and Marketing Activities,” Marketing Science, 30 (4), 568–85.
   Web of Science ®Google Scholar
• Friedman, Jerome H. (1991), “Multivariate Adaptive Regression Splines,” Annals of Statistics, 19 (1), 1–67.
   Web of Science ®Google Scholar
• Grabner, Isabella, and Frank Moers (2015), “Determinants and Consequences of Budget Reallocations: Evidence from the Consumer Goods Industry,” https://ssrn.com/abstract=2595666.
   Google Scholar
• Harkins, Stephen G., and Richard E. Petty (1981), “Effects of Source Magnification of Cognitive Effort on Attitudes: An Information-Processing View,” Journal of Personality and Social Psychology, 40 (3), 401–13.
   Web of Science ®Google Scholar
• Hastie, Trevor, Robert Tibshirani, and Jerome Friedman (2001), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, New York: Springer Science and Business Media.
   Google Scholar
• Havlena, William, Robert Cardarelli, and Michelle De Montigny (2007), “Quantifying the Isolated and Synergistic Effects of Exposure Frequency for TV, Print, and Internet Advertising,” Journal of Advertising Research, 47 (3), 215–21.
   Web of Science ®Google Scholar
• Jagpal, Harsharanjeet S. (1981), “Measuring Joint Advertising Effects in Multiproduct Firms,” Journal of Advertising Research, 21 (1), 65–69.
   Web of Science ®Google Scholar
• Kumar, V., JeeWon Brianna Choi, and Mallik Greene (2017), “Synergistic Effects of Social Media and Traditional Marketing on Brand Sales: Capturing the Time-Varying Effects,” Journal of the Academy of Marketing Science, 45 (2), 268–88.
   Web of Science ®Google Scholar
• Lewis, P.A.W., and J.G. Stevens (1991), “Nonlinear Modeling of Time Series Using Multivariate Adaptive Regression Splines (MARS),” Journal of the American Statistical Association, 86 (416), 864–77.
   Web of Science ®Google Scholar
• Marketing Science Institute (2016), “Marketing Science Institute Research Priorities 2016–2018,” https://www.msi.org/uploads/articles/MSI_RP16-18.pdf.
   Google Scholar
• Mitchell, Andrew A., and Jerry C. Olson (1977), “Cognitive Effects of Advertising Repetition,” In North American Advances in Consumer Research, William D. Perreault Jr., ed., vol. 4, Atlanta: Association for Consumer Research, 213–20.
   Google Scholar
• Moore, David J., and Richard Reardon (1987), “Source Magnification: The Role of Multiple Sources in the Processing of Advertising Appeals,” Journal of Marketing Research, 24 (4), 412–17.
   Web of Science ®Google Scholar
• Naik, Prasad A., and Kay Peters (2009), “A Hierarchical Marketing Communications Model of Online and Offline Media Synergies,” Journal of Interactive Marketing, 23 (4), 288–99.
   Web of Science ®Google Scholar
• Naik, Prasad A., and Kalyan Raman (2003), “Understanding the Impact of Synergy in Multimedia Communications,” Journal Of Marketing Research, 40 (4), 375–88.
   Web of Science ®Google Scholar
• Nguyen, Dung (1985), “An Analysis of Optimal Advertising under Uncertainty,” Management Science, 31 (5), 622–33.
   Web of Science ®Google Scholar
• Pantelidaki, Stefania, and Derek W. Bunn (2005), “Development of a Multifunctional Sales Response Model with the Diagnostic Aid of Artificial Neural Networks,” Journal of Forecasting, 24 (7), 505–21.
   Web of Science ®Google Scholar
• Pilotta, Joseph J., and Don Schultz (2005), “Simultaneous Media Experience and Synesthesia,” Journal of Advertising Research, 45 (1), 19–26.
   Web of Science ®Google Scholar
• Porta, Miquel (ed.) (2008), A Dictionary of Epidemiology, New York: Oxford University Press.
   Google Scholar
• Raman, Kalyan, and Prasad A. Naik (2004), “Long-Term Profit Impact of Integrated Marketing Communications Program,” Review of Marketing Science, 2 (1), published electronically, doi:10.2202/1546-5616.1014.
   Google Scholar
• Rothman, Kenneth J. (1974), “Synergy and Antagonism in Cause-Effect Relationships,” American Journal of Epidemiology, 99 (6), 385–88.
   PubMed Web of Science ®Google Scholar
• Sridhar, Shrihari, Frank Germann, Charles Kang, and Rajdeep Grewal (2016), “Relating Online, Regional, and National Advertising to Firm Value,” Journal of Marketing, 80 (4), 39–55.
   Web of Science ®Google Scholar
• Stafford, Marla Royne, Eric M. Lippold, and C. Todd Sherron (2003), “The Contribution of Direct Mail Advertising to Average Weekly Unit Sales,” Journal of Advertising Research, 43 (2), 173–79.
   Web of Science ®Google Scholar
• Taylor, Jennifer, Rachel Kennedy, Colin McDonald, Laurent Larguinat, Yassine El Ouarzazi, and Nassim Haddad (2013), “Is the Multi-Platform Whole More Powerful Than Its Separate Parts?,” Journal of Advertising Research, 53 (2), 200–11.
   Web of Science ®Google Scholar
• Tellis, Gerard J. (1988), “Advertising Exposure, Loyalty, and Brand Purchase: A Two-Stage Model of Choice,” Journal of Marketing Research, 25 (2), 134–44.
   Web of Science ®Google Scholar
• Terui, Nobuhiko, and Masataka Ban (2008), “Modeling Heterogeneous Effective Advertising Stock Using Single-Source Data,” Quantitative Marketing and Economics, 6 (4), 415–38.
   Web of Science ®Google Scholar
• Tull, Donald S., Van R. Wood, Dale Duhan, Tom Gillpatrick, Kim R. Robertson, and James G. Helgeson (1986), “‘Leveraged’ Decision Making in Advertising: The Flat Maximum Principle and Its Implications,” Journal of Marketing Research, 23 (1), 25–32.
   Web of Science ®Google Scholar
• Unnava, H. Rao, and Robert E. Burnkrant (1991), “Effects of Repeating Varied Ad Executions or Brand Name Memory,” Journal of Marketing Research, 28 (4), 406–16.
   Web of Science ®Google Scholar
• Vakratsas, Demetrios, Fred M. Feinberg, Frank M. Bass, and Gurumurthy Kalyanaram (2004), “The Shape of Advertising Response Functions Revisited: A Model of Dynamic Probabilistic Thresholds,” Marketing Science, 23 (1), 109–19.
   Web of Science ®Google Scholar
• Vakratsas, Demetrios, and Zhenfeng Ma (2005), “A Look at the Long-Run Effectiveness of Multimedia Advertising and Its Implications for Budget Allocation Decisions,” Journal of Advertising Research, 45 (2), 241–54.
   Web of Science ®Google Scholar