This article estimates dynamic diffusion systems developed earlier by Mesak and Darrat (2002) for newsubscriber consumer services. Each system consists of two equations, one for the retailer adoption process and another for the consumer adoption process. Using diffusion annual data related to the cable TV industry in the United States, three alternative interactive systems based on the Bass (1969) model are estimated and contrasted in terms of their predictive power. The empirical results support a two-way diffusion system that includes price. The incorporation of price proves critical for the system’s predictive power. In addition, a noninteractive, two-simultaneous-equations model as well as a single-equation model fail to provide adequate representation of the data.
Get full access to this article
View all access options for this article.
References
1.
Amemiya, T. (1985), Advanced Econometrics.Cambridge, MA: Harvard University Press.
2.
Bass, F. M. (1969), “A New Product Growth Model for Consumer Durables,” Management Science, 15, 215-227.
3.
Bass, F. M. (1980), “The Relationship between Diffusion Curves, Experience Curves, and Demand Elasticities for Consumer Durable Technological Innovations,” Journal of Business, 53, 551-567.
4.
Bass, F. M. and A. V. Bultez (1983), “A Note on Optimal Strategic Pricing of Technological Innovations,” Marketing Science, 1, 371-378.
5.
Bass, F. M., A. V. Bultez, D. Jain, and T. Krishnan (2000), “Modeling the Marketing-Mix Influence in New-Product Diffusion,” in New-Product Diffusion Models, V. Mahajan, E. Muller, and Y. Wind, eds. Boston: Kluwer.
6.
Bass, F. M., A. V. Bultez, D. Jain, T. Krishnan, T. V. Krishnan, and D. C. Jain (1994), “Why the Bass Model Fits without Decision Variables,” Marketing Science, 13 (Summer), 203-223.
7.
Bhargava, S. C., R. K. Bhargava, and A. Jain (1991),“Requirement of Dimensional Consistency in Model Equations: Diffusion Models Incorporating Price and Their Applications,” Technological Forecasting and Social Change, 41, 177-188.
8.
Bleaney, M. (1990),“Some Comparisons of the Relative Power of Simple Tests for Structural Change in Regression Models,” Journal of Forecasting, 9, 437-444.
9.
Bliemel, F. (1973), “Theil’s Forecast Accuracy Coefficient: A Clarification,” Journal of Marketing Research, 10, 444-446.
10.
Bottomley, P. A. and R. Fildes (1998), “The Role of Prices in Models of Innovation Diffusion,” Journal of Forecasting, 17, 539-555.
11.
Bronnenberg, B. J., V. Mahajan, and W. R. Vanhonacker (2000), “The Emergence of Market Structure in New Repeat-Purchase Categories: The Interplay of Market Share and Retailer Distribution,” Journal of Marketing Research, 37 (February), 16-31.
12.
Chen, Yu-Min and Hirokaz Takada (1994), “Estimating the Geographic Diffusion of the Video-Cassette Recorder Market,” Empirical Economics, 19, 451-472.
13.
Curry, David J., Suresh Divakar, Sharat K. Mathur, and Charles White-mark (1995), “BVAR as a Category Management Tool: An Illustration and Comparison with Alternative Techniques,” Journal of Forecasting, 14, 181-199.
14.
Danaher, P., B. Hardie, and W. Putsis (2001), “Marketing Mix Variables and the Diffusion of Successive Generations of a Technological Innovation,” Journal of Marketing Research, 38, (November), 501-514.
15.
Dolan, R. J. and A. P. Jeuland (1981), “Experience Curves and Dynamic Demand Models: Implications for Optimal Pricing Strategies,” Journal of Marketing, 45, 52-62.
16.
Eliashberg, Jehoshua and Kristiaan Helsen (1994), “Modeling Lead/Lag Phenomena in Global Marketing: The Case of VCRs,” working paper, University of Pennsylvania.
17.
Enders, W. (1995), Applied Econometric Time Series.New York: John Wiley.
18.
Engle, R. F., D. F.Hendry, and J. F. Richard (1983), “Exogeneity,” Econometrica, 51 (March), 277-304.
19.
Erickson, G. M. (1992), “Empirical Analysis of Closed-Loop Duopoly Advertising Strategies,” Management Science, 38 (December), 1732-1749.
20.
General Accounting Office (1990), Follow-Up National Survey of Cable Television Rates and Services. GAO/RCED-90-199.
21.
Granger, C. W. J. (1969), “Investigating Causal Relations by Econometric Models and Cross-Spectral Methods,” Econometrica, 37 (3), 424-438.
22.
Greene, W. H. (1997), Econometric Analysis.Englewood Cliffs, NJ: Prentice Hall.
23.
Hirsch, A. A. and M. C.Lovell (1969), Sales Anticipation and Inventory Behavior. New York: John Wiley.
24.
Hirschman, E. C. and R. W. Stampfl (1980), “Roles of Retailing in the Diffusion of Popular Culture: Microperspectives,” Journal of Retailing, 56(1), 16-36.
25.
Ireland, N. and P. Stoneman (1986), “Technological Diffusion, Expectations and Welfare,” Oxford Economic Papers, 38, 283-304.
26.
Jain, D. C., V. Mahajan, and E. Muller (1991), “Innovation Diffusion in the Presence of Supply Restrictions,” Marketing Science, 10(Winter), 83-90.
27.
Jain, D. C., V. Mahajan, E. Muller and R. C. Rao (1990), “Effect of Price on the Demand for Durables: Modeling, Estimation and Findings,” Journal of Business and Economic Statistics, 8, 163-170.
28.
Jones, J. M. and C. H. Mason (1990),“The Role of Distribution in the Dif fusion of New Durable Consumer Products,” working paper, Marketing Science Institute, Cambridge, MA.
29.
Jones, J. M., C. H. Mason and C.J.Ritz (1991), “Incorporating Distribution in to New Product Diffusion Models,” International Journal of Research in Marketing, 8, 91-112.
30.
Kalish, S. (1983), “Monopolist Pricing with Dynamic Demand and Production Cost,” Marketing Science, 2, 135-160.
31.
Kamakura, W. and S. K. Balasubramanian (1988), “Long-Term View of the Diffusion of Durables,” International Journal of Research in Marketing, 5, 1-13.
32.
Krishnan, T. V., F. M. Bass, and D. C. Jain (1999),“Optimal Pricing Strategy for New Products,” Management Science, 45 (12), 1650-1663.
33.
Krishnan, T. V., F. M. Bass, D. C. Jain, and V. Kumar (2000), “Impact of a Late Entrant on the Diffusion of a New Product/Service,” Journal of Marketing Research, 37, 269-278.
34.
Leeflang, P. S. H., D. R. Wittink, M. Wedel, and P. A. Neart (2000), Building Models for Marketing Decisions. Boston: Kluwer.
35.
Mahajan, V. and E. Muller (1994), “Innovation Diffusion in a Borderless Global Market: Will the 1992 Unification of the European Community Accelerate Diffusion of New Ideas, Products, and Technologies?,” Technological Forecasting and Social Change, 45, 221-235.
36.
Mahajan, V., E. Muller, and F. M. Bass (1990), “New Product Diffusion Models: A Review and Directions for Research,” Journal of Marketing, 54, 1-26.
37.
Mahajan, V., E. Muller, and F. M. Bass, and Y. Wind (2000), New-Product Diffusion Models. Boston: Kluwer.
38.
McConnell, B. (2001), “Merger Modeling,” Broadcasting & Cable, New York, November, 38.
39.
Meade, N. and T. Islam (1998), “Technological Forecasting: Model Se lection, Model Stability, and Combining Models,” Management Science, 44 (8), 1115-1130.
40.
Mesak, H. I. (1996), “Incorporating Price, Advertising and Distribution in Diffusion Models of Innovation: Some Theoretical and Empirical Results,” Computers and Operations Research, 23 (10), 1007-1023.
41.
Mesak, H. I. and A. F. Darrat (2002),“Optimal Pricing of New Subscriber Ser vices under Interdependent Adoption Processes,” Journal of Service Research, 5 (November), 140-153.
42.
Montgomery, D. B. (1972),“FORAC MOD I: Program for Forecast Evaluation Statistics,” Journal of Marketing Research, 9 (May), 200.
43.
Parker, P. M. (1992), “Price Elasticity Dynamics over the Adoption Life Cycle,” Journal of Marketing Research, 24, 358-367.
44.
Phillips, P. C. B. (1986), “Understanding Spurious Regression in Econometrics,” Journal of Econometrics, 33, 311-340.
45.
Pindyck, R. S. and D. L. Rubinfeld (1998), Econometric Models and Economic Forecasts. Boston: McGraw-Hill.
46.
Putsis, W. P., Jr., S. K. Balasubramanian, E. H. Kaplan, and S. K. Sen (1997), “Mixing Behavior in Cross-Country Diffusion,” Marketing Science, 16 (4), 354-369.
47.
Radas, S. and S. M. Shugan (1998), “Seasonal Marketing and Timing New Product Introductions,” Journal of Marketing Research, 35 (Au-gust), 296-315.
48.
Rao, S. K. (1985), “An Empirical Comparison of Sales Forecasting Models,” Journal of Product Innovation Management, 11, 201-212.
49.
Redmond, W. H. (1994), “Diffusion at Sub-National Levels: A Regional Analysis of New Product Growth,” Journal of Product Innovation Management, 11, 201-212.
50.
Robinson, B. and C. Lakhani (1975), “Dynamic Price Models for New Product Planning,” Management Science, 10, 1113-1122.
Rust, R. T. and D. C. Schmittlein (1985), “A Bayesian Cross-Validated Likelihood Method for Comparing Alternative Specifications of Quantitative Models,” Marketing Science, 4 (Winter), 20-40.
53.
Rust, R. T., D. C. Schmittlein, A. J. Zahorik, and T. L. Keiningham (1995), “Return on Quality (ROQ): Making Service Quality Financially Accountable,” Journal of Marketing, 59 (April), 58-70.
54.
Simon, H. (1989), Price Management. New York: North-Holland.
55.
Sims, C. A. (1972),“Money, Incomeand Causality,” American Economic Review, 62, 540-552.
56.
Speece, M. and D. MacLachlan (1992), “Forecasting Fluid Milk Package Type with a Multi-Generation New-Product Diffusion Model,” IEEE Transactions on Engineering Management, 39 (March), 169-175.
57.
Stoneman, P. and N. J. Ireland (1983), “The Role of Supply Factors in the Diffusion of New Process Technology,” The Economic Journal, Conference Supplement, 65-77.
58.
Theil, H. (1965), Economic Forecasts and Policy.Amsterdam: North-Holland.
59.
Theil, H. (1966), Applied Economic Forecasts.Amsterdam: North-Holland.
60.
Thirtle, C. and V.Ruttan (1987), The Role of Demand and Supply in the Generation and Diffusion of Technical Change.New York: Harwood Academic Publishers.
61.
Thompson, G. L. and J. T.Teng (1984),“Optimal Pricingand Advertising Policies for New Product Oligopoly Models,” Marketing Science, 3 (Spring), 148-168.
62.
Wheatley, M. (2001), “Sound Systems,” CIO, Framingham, March 1, 64-68.
63.
Young, P. (1993), “Technological Growth Curves: A Comparison of Forecasting Models,” Technological Forecasting and Social Change, 44 (4), 375-389.
64.
Zanias, George P. (1994), “The Long-Run, Causality, and Forecasting in the Advertising-Sales Relationships,” Journal of Forecasting, 13, 601-610.
