Practice Prize Article—CHAN4CAST: A Multichannel, Multiregion Sales Forecasting Model and Decision Support System for Consumer Packaged Goods

References

• Abraham M., Lodish L. PROMOTER: an automated promotion evaluation system. Marketing Sci. (1987) 6(2):101–123Link, Google Scholar
• Abraham M., Lodish L. An implemented system for improving promotion productivity using store scanner data. Marketing Sci. (1993) 12(3):248–269Link, Google Scholar
• Alavi Maryam, Joachimsthaler Erich A. Revisiting DSS implementation research: a meta-analysis of the literature and suggestions for researchers. MIS Quart. (1992) 16(1):95–116Crossref, Google Scholar
• Albers Sonke. A framework for analysis of profit contribution variance between actual and plan. Internat. J. Res. Marketing (1998) 15(2):109–122Crossref, Google Scholar
• Allenby Greg M., Shivley Thomas S., Yang Sha, Garratt Mark J. A choice model for packaged goods: dealing with discrete quantities and quantity discounts. Marketing Sci. (2004) 23(1):95–108Link, Google Scholar
• Bell D., Chiang J., Padmanabhan V. The decomposition of promotional response: an empirical generalization. Marketing Sci. (1999) 18(4):504–526Link, Google Scholar
• Besanko D., Gupta S., Jain D. Logit demand estimation under competitive pricing behavior: an equilibrium framework. Management Sci. (1998) 44(11):1533–1547Link, Google Scholar
• Blattberg R. C., Levin A. Modeling the effectiveness and profitability of trade promotions. Marketing Sci. (1987) 6(2):124–146Link, Google Scholar
• Blattberg R. C., Wisniewski K. Price-induced patterns of competition. Marketing Sci. (1989) 8(4):291–309Link, Google Scholar
• Bronnenberg B., Mela C. F. Market rollout and retail adoption of new brands. Marketing Sci. (2004) 23(4):490–499Link, Google Scholar
• Bolton Ruth N., Shankar Venkatesh. An empirically derived taxonomy of retailer pricing and promotion strategies. J. Retailing (2003) 79(4):213–224Crossref, Google Scholar
• Bucklin R., Gupta S. Commercial use of UPC scanner data: industry and academic perspectives. Marketing Sci. (1999) 18(3):247–273Link, Google Scholar
• Christen M., Gupta S., Porter J., Staelin R., Wittink D. Using market level data to understand promotion effects in a nonlinear model. J. Marketing Res. (1997) 34(3):322–334Crossref, Google Scholar
• Curley Kathleen F., Gremillion Lee L. The role of the champion in DSS implementation. Inform. Management (1983) 6(4):203–209Crossref, Google Scholar
• Dube J. P. Multiple discreteness and product differentiation: demand for carbonated soft drinks. Marketing Sci. (2004) 23(1):66–81Link, Google Scholar
• Elrod T., Russell G., Shocker A., Rao V., Bayus B., Carroll D., Kamakura W., Shankar V. Inferring market structure from customer response to competing and complementary products. Marketing Lett. (2002) 13(3):221–232Crossref, Google Scholar
• Fader P. S., Hardie B. S., Armstrong J. S. Forecasting trial sales of new consumer packaged goods. Principles of Forecasting (2001) (Kluwer, Newell, MA) 613–630Crossref, Google Scholar
• Fader P. S., Hardie B. S., Huang Chun-Yao. A dynamic changepoint model for new product sales forecasting. Marketing Sci. (2004) 23(1):50–65Link, Google Scholar
• Fockens E., Leeflang P., Wittink D. A comparison and exploration of the forecasting accuracy of a nonlinear model at different levels of aggregation. Internat. J. Forecasting (1994) 10(2):245–261Crossref, Google Scholar
• Greene W.Econometric Analysis (2003) 5th ed.(Prentice-Hall, Inc., Upper Saddle River, NJ) Google Scholar
• Guadagni P. H., Little J. D. C. A logit model of brand choice calibrated on scanner data. Marketing Sci. (1983) 2(Summer):327–351Google Scholar
• Hoch S., Kim B., Montgomery A., Rossi P. Determinants of store-level price elasticity. J. Marketing Res. (1995) 32(1):17–29Crossref, Google Scholar
• Inman J. J., Shankar V., Ferraro R. “You are where you shop”: an examination of product category-channel associations and the drivers of cross-channel variation in shopping behavior. (2002) . Working Paper Series 02-117, Marketing Science Institute, Boston, MAGoogle Scholar
• Inman J. J., Shankar V., Ferraro R. The roles of channel-category associations and geo-demographics in channel patronage. J. Marketing (2004) 68(2):51–71Crossref, Google Scholar
• Leeflang P. S. H., Wittink D. R. Building models for marketing decisions: past, present and future. Internat. J. Res. Marketing (2000) 17(2–3):105–126Crossref, Google Scholar
• Lilien G., Rangaswamy A.Marketing Engineering (2002) 2nd ed.(Prentice Hall, Upper Saddle River, NJ) Google Scholar
• Little J. D. C. Models and managers: the concept of a decision calculus. Management Sci. (1970) 16(8):B466–Link, Google Scholar
• Little J. D. C. Comments on “Models and managers: the concept of a decision calculus.”. Management Sci. (2004) 50(12):1854–1860Link, Google Scholar
• Morris Steven A., Marshall Thomas E. Perceived control in information systems. J. Organ. End User Comput. (2004) 16(2):28–56Crossref, Google Scholar
• Naik Prasad A., Raman Kalyan, Winer Russell S. Planning marketing-mix strategies in the presence of interaction effects. Marketing Sci. (2005) 24(1):25–34Link, Google Scholar
• Roberts John H., Nelson Charles J., Morrison Pamela D. A prelaunch diffusion model for evaluating market defense strategies. Marketing Sci. (2005) 24(1):38–56Link, Google Scholar
• Russell G., Ratneshwar S., Shocker A. D., Bell D., Bodapati A., Degeratu A., Hilderbrandt L., Kim N., Ramaswami S., Shankar V. Multiple category decision-making: review and synthesis. Marketing Lett. (1999) 10(3):319–332Crossref, Google Scholar
• Shankar Venkatesh, Bolton Ruth N. An empirical analysis of determinants of retailer pricing strategy. Marketing Sci. (2004) 23(1):28–49Link, Google Scholar
• Silk A. J., Urban G. L. Pretest market evaluation of new packaged goods: a model and measurement methodology. J. Marketing Res. (1978) 15(2):171–191Crossref, Google Scholar
• van Bruggen G. H., Smidts A., Wierenga B. Improving decision making by means of a marketing decision support system. Management Sci. (1998) 44(5):645–658Link, Google Scholar
• van Heerde H., Gupta S., Wittink D. Is 75% of the sales promotion bump due to brand switching? No, only 33% is. J. Marketing Res. (2003) 40(4):481–491Crossref, Google Scholar
• van Heerde H., Leeflang P. S. H., Wittink D. How promotions work: SCAN*PRO-based evolutionary model building. Schmalenbach Bus. Rev. (2002) 54(3):198–220Crossref, Google Scholar
• Wierenga B., van Bruggen G. H. Developing a customized decision-support system for brand managers. Interfaces (1997) 3(Part 2):S128–S145Google Scholar
• Wierenga B., van Bruggen G. H.Marketing Management Support Systems: principles, Tools, and Implementation (2000) (Kluwer Academic Publishers, Boston, MA) Crossref, Google Scholar
• Wierenga B., van Bruggen G. H., Staelin R. The success of marketing management support systems. Marketing Sci. (1999) 18(3):196–207Link, Google Scholar
• Wittink D., Addona M., Hawkes W., Porter J. C. SCAN*PRO: the estimation, validation, and use of promotional effects based on scanner data. (1988) . Working paper, ACNielsen, Schaumburg, ILGoogle Scholar
• Wu D. Alternative tests of independence between stochastic repressors and disturbances. Econometrica (1973) 41(4):733–750Crossref, Google Scholar