A Piecewise-Diffusion Model of New-Product Demands

The Bass Model (BM) is a widely-used framework in marketing for the study of new-product sales growth. Its usefulness as a demand model has also been recognized in production, inventory, and capacity-planning settings. The BM postulates that the cumulative number of adopters of a new product in a large population approximately follows a deterministic trajectory whose growth rate is governed by two parameters that capture (i) an individual consumer’s intrinsic interest in the product, and (ii) a positive force of influence on other consumers from existing adopters. A finite-population purebirth-process (re)formulation of the BM, called the Stochastic Bass Model (SBM), was proposed recently by the author in a previous paper, and it was shown that if the size of the population in the SBM is taken to infinity, then the SBM and the BM agree (in probability) in the limit. Thus, the SBM “expands” the BM in the sense that for any given population size, it is a well-defined model. In this paper, we exploit this expansion and introduce a further extension of the SBM in which demands of a product in successive time periods are governed by a history-dependent family of SBMs (one for each period) with different population sizes. A sampling theory for this extension, which we call the Piecewise-Diffusion Model (PDM), is also developed. We then apply the theory to a typical product example, demonstrating that the PDM is a remarkably accurate and versatile framework that allows us to better understand the underlying dynamics of new-product demands over time. Joint movement of price and advertising levels, in particular, is shown to have a significant influence on whether or not consumers are “ready” to participate in product purchase. Subject classifications: marketing: new products, buyer behavior, pricing; probability: diffusion; inventory/production: stochastic, nonstationary demand. Area of review: Manufacturing, Service, and Supply Chain Operations. History: Received August 2003; revision received September 2004; accepted July 2005.

[1]  Shun-Chen Niu,et al.  A Stochastic Formulation of the Bass Model of New-Product Diffusion , 2002 .

[2]  F. Bass The Relationship between Diffusion Rates, Experience Curves, and Demand Elasticities for Consumer Durable Technological Innovations , 1980 .

[3]  Vijay Mahajan,et al.  Innovation Diffusion Models of New Product Acceptance: A Reexamination , 1985 .

[4]  Vijay Mahajan,et al.  New Product Diffusion Models in Marketing: A Review and Directions for Research: , 1990 .

[5]  D. Jain,et al.  Effect of Price on the Demand for Durables: Modeling, Estimation, and Findings , 1990 .

[6]  Fred Böker,et al.  A Stochastic First Purchase Diffusion Model: A Counting Process Approach , 1987 .

[7]  Hirofumi Matsuo,et al.  Forecasting and Inventory Management of Short Life-Cycle Products , 1996, Oper. Res..

[8]  Robert A. Peterson,et al.  Models for innovation diffusion , 1985 .

[9]  Philip M. Parker,et al.  Aggregate diffusion forecasting models in marketing: A critical review , 1994 .

[10]  S. Ethier,et al.  Markov Processes: Characterization and Convergence , 2005 .

[11]  Sheldon M. Ross,et al.  Introduction to Probability Models (4th ed.). , 1990 .

[12]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[13]  Christos H. Skiadas,et al.  A stochastic Bass innovation diffusion model for studying the growth of electricity consumption in Greece , 1997 .

[14]  V. Mahajan,et al.  Innovation Diffusion and New Product Growth Models in Marketing , 1979 .

[15]  Charlotte H. Mason,et al.  Technical Note---Nonlinear Least Squares Estimation of New Product Diffusion Models , 1986 .

[16]  V. Mahajan,et al.  Innovation Diffusion Models of New Product Acceptance. , 1987 .

[17]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[18]  D. Lehmann,et al.  Extent and Impact of Incubation Time in New Product Diffusion , 1999 .

[19]  Frank M. Bass,et al.  A New Product Growth for Model Consumer Durables , 2004, Manag. Sci..

[20]  K. Isii,et al.  On a stochastic model concerning the pattern of communication , 1959 .

[21]  Trichy V. Krishnan,et al.  Optimal Pricing Strategy for New Products , 1999 .

[22]  Vijay Mahajan,et al.  Chapter 8 New-product diffusion models , 1993, Marketing.

[23]  F. Bass,et al.  A diffusion theory model of adoption and substitution for successive generations of high-technology products , 1987 .

[24]  Sheldon M. Ross,et al.  Introduction to probability models , 1975 .

[25]  D. Horsky,et al.  Advertising and the Diffusion of New Products , 1983 .

[26]  Bruce R. Robinson,et al.  Dynamic Price Models for New-Product Planning , 1975 .

[27]  Shlomo Yitzhaki,et al.  The Diffusion of Innovations: A Methodological Reappraisal , 1982 .

[28]  Christian Terwiesch,et al.  Managing Demand and Sales Dynamics in New Product Diffusion Under Supply Constraint , 2002, Manag. Sci..

[29]  Vijay Mahajan,et al.  Maximum Likelihood Estimation for an Innovation Diffusion Model of New Product Acceptance , 1982 .

[30]  Dipak C. Jain,et al.  Why the Bass Model Fits without Decision Variables , 1994 .

[31]  Sunil Kumar,et al.  Diffusion of Innovations Under Supply Constraints , 2003, Oper. Res..

[32]  S. Kalish A New Product Adoption Model with Price, Advertising, and Uncertainty , 1985 .

[33]  M. Meler,et al.  New product diffusion models , 1995 .