A Critical Review of Marketing Research on Diffusion of New Products

We critically examine alternate models of the diffusion of new products and the turning points of the diffusion curve. On each of these topics, we focus on the drivers, specifications, and estimation methods researched in the literature. We discover important generalizations about the shape, parameters, and turning points of the diffusion curve and the characteristics of diffusion across early stages of the product life cycle. We point out directions for future research. Because new products affect every aspect of the life of individuals, communities, countries, and economies, the study of the diffusion of innovations is of vital importance. Researchers have studied this topic in various disciplines, including marketing, economics, medicine, agriculture, sociology, anthropology, geography, and technology management. We present a critical review of research on the diffusion of new products primarily in the marketing literature, but also in the economics and geography literature. We use the word product broadly to cover any good, service, idea, or person. We distinguish the term new product from the broader term innovation, which refers to both new product and new method, practice, institution, or social entity. Even though we restrict our review to the marketing literature, which focuses on the diffusion of new products, the implications of our review may hold as well as for the study of the diffusion of innovations in other disciplines. The marketing literature on this topic is vast, dating back at least as early as the publication by Fourt and Woodlock (1960). The term diffusion has been used differently in two groups of literatures. Within economics and most nonmarketing disciplines, diffusion is defined as the spread of an innovation across social groups over time (Brown, 1981; Stoneman, 2002). As such, the phenomenon is separate from the drivers, which can be consumer income, the product’s price, word-of-mouth communication, and so on. In marketing and communication, diffusion typically has come to mean the communication of an innovation through the population (Golder and Tellis, 1998; Mahajan, Muller, and Wind, 2000a; Mahajan, Muller, and Bass, 1990; Rogers 1995). In this sense, the phenomenon (spread of a product) is synonymous with its underlying driver (communication). The Webster (2004) definition of the noun “diffusion” is “the spread of a cultural or technological practice or innovation from one region or people to another, as by trade or conquest” and the verb “diffusing” is “pour, spread out or disperse in every direction; spread or scatter widely.” This latter interpretation is synonymous with the term’s use in economics and most other disciplines. In addition, some researchers in marketing have subscribed to the definition used in economics (Bemmaor, 1994; Dekimpe, Parker, and Sarvary, 2000a; Van den Bulte and 40 DEEPA CHANDRASEKARAN AND GERARD J. TELLIS Stremersch, 2004). Hence, in this review, we define diffusion as the spread of an innovation across markets over time. Researchers commonly measure diffusion using the sales and especially the market penetration of a new product during the early stages of its life cycle. To characterize this phenomenon carefully, we adopt the definitions of the stages and turning points of the product’s life cycle by Golder and Tellis (2004): 1. Commercialization is the date a new product is first sold. 2. Takeoff is the first dramatic and sustained increase in a new product’s sales. 3. Introduction is the period from a new product’s commercialization until its takeoff. 4. Slowdown is the beginning of a period of level, slowly increasing, or temporarily decreasing product sales after takeoff. 5. Growth is the period from a new product’s takeoff until its slowdown. 6. Maturity is the period from a product’s slowdown until sales begin a steady decline. Hence, there are two key turning points in the diffusion curve: takeoff and slowdown. Prior reviews address various aspects of the marketing literature on the diffusion of new products. For example, Mahajan, Muller, and Bass (1990) provide an excellent overview of the Bass model, its extensions, and some directions for further research. Parker (1994) provides an overview of the Bass model and evaluates the various estimation techniques, forecasting abilities, and specification improvements of the model. Mahajan, Muller, and Bass (1995) summarize the generalizations from applications of the Bass model. An edited volume by Mahajan, Muller, and Wind (2000b) covers in depth various topics in diffusion models, such as specification, estimation, and applications. Sultan, Farley, and Lehmann (1990) and Van den Bulte and Stremersch (2004) meta-analyze the diffusion parameters of the Bass model. The current review differs from prior reviews in two important aspects. First, the prior reviews focus on the S-curve of cumulative sales of a new product, mostly covering growth. This review focuses on phenomena besides the S-curve, such as takeoff and slowdown. Second, the above reviews focus mainly on the Bass model. This review considers the Bass model as well as other models of diffusion and drivers of new product diffusion other than communication. Our key findings and the most useful part of our study is the discovery of potential generalizations from past research. For the benefit of readers who are familiar with this topic, we present these generalizations before details of the measures, models, and methods used in past research. (Readers who are unfamiliar with the topic may want to read the Potential Generalizations section last). Therefore, we organize the rest of the chapter as follows. In the next section, we summarize potential generalizations from prior research. In the third section, we point out limitations of past research and directions for future research. In the fourth section, we evaluate key models and drivers of the diffusion curve. In the fifth section, we evaluate models of the key turning points in diffusion: takeoff and slowdown. Potential Generalizations We use the term potential generalizations or regularities to describe empirical findings with substantial support. By substantial, we mean that support comes from reviews or meta-analyses of the literature or individual studies with a large sample of over ten categories or ten countries. Table 2.1 lists the studies on which the potential generalizations are based. This section covers important findings about the shape of the diffusion curve, parameters of the Bass models, the turning points of diffusion, and findings across stages of the diffusion curve. MARKETING RESEARCH ON DIFFUSION OF NEW PRODUCTS 41 Shape of the Diffusion Curve The most important and most widely reported finding about new product diffusion relates to the shape of the diffusion curve (see Figure 2.1). Numerous studies in a variety of disciplines suggest that (with the exception of entertainment products) the plot of cumulative sales of new products against time is an S-shaped curve (e.g., Mahajan, Muller, and Bass 1990; Mahajan, Muller, and Wind, 2000a). Parameters of the Bass Model Most of the marketing studies use the Bass diffusion model to capture the S-shaped curve of new products sales (see later section for explanation). This model has three key parameters: the coefficient of innovation or external influence (p), the coefficient of imitation or internal influence (q), and the market potential (α or m). Table 2.1 Studies Included for Assessing Potential Generalizations Authors Categories Countries Gatignon, Eliashberg, and 6 consumer durables 14 European countries Robertson (1989) Mahajan, Muller, and Bass (1990) Numerous studies Sultan, Farley, and Lehmann (1990) 213 applications United States, European countries Helsen, Jedidi, and DeSarbo (1993) 3 consumer durables 11 European countries and United States Ganesh and Kumar (1996) 1 industrial product 10 European countries, United States, and Japan Ganesh, Kumar, Subramaniam (1997) 4 consumer durables 16 European countries Golder and Tellis (1997) 31 consumer durables United States Putsis et al., (1997) 4 consumer durables 10 European countries Dekimpe, Parker, and Sarvary (1998) 1 service 74 countries Kumar, Ganesh, and Echambadi (1998) 5 consumer durables 14 European countries Golder and Tellis (1998) 10 consumer durables United States Kohli, Lehmann, and Pae (1999) 32 appliances, house United States wares and electronics Dekimpe, Parker, and Sarvary (2000) 1 innovation More than 160 countries Mahajan, Muller, and Wind (2000) Numerous studies Van den Bulte (2000) 31 consumer durables United States Talukdar, Sudhir, and Ainslie (2002) 6 consumer durables 31 countries Agarwal and Bayus (2002) 30 innovations United States Goldenberg, Libai, and Muller (2002) 32 innovations United States Tellis, Stremersch, and Yin (2003) 10 consumer durables 16 European countries Golder and Tellis (2004) 30 consumer durables United States Stremersch and Tellis (2004) 10 consumer durables 16 European countries Van den Bulte and Stremersch (2004) 293 applications 28 countries <<PLEASE SPECIFIY 2000a OR 2000b>> <<PLEASE SPECIFIY 2000a OR 2000b>> 42 DEEPA CHANDRASEKARAN AND GERARD J. TELLIS Coefficient of Innovation • The mean value of the coefficient of innovation for a new product lies between 0.0007 and .03 (Sultan, Farley, and Lehmann, 1990; Talukdar, Sudhir, and Ainslie, 2002; Van den Bulte and Stremersch, 2004). • The mean value of the coefficient of innovation for a new product is 0.001 for developed countries and 0.0003 for developing countries (Talukdar, Sudhir, and Ainslie, 2002). • The coefficient of innovation is higher for European countries than for the United States (Sultan, Farley, and Lehmann, 1990). Coefficient of Imitation • The mean value of the coefficient of imitation for a new product lies between 0.38 and 0.53 (Sultan, Farley, and Lehmann, 1990; Talukdar, Sudhir, and Ainslie, 2002; Van den Bulte and Stremersch, 2004). • Indu