در آستانه: نقش عملکرد و سازگاری در نفوذ در بازار محصولات جدید خلاقانه

Both academicians and practitioners agree that there exists a critical threshold to cross for an innovative new product to be able to achieve ultimate market penetration. In this article, the authors characterize the threshold as depending upon innovation characteristics: performance and compatibility, in particular. Based on the insights from evolutionary games, several numerical simulations are conducted to investigate how the critical threshold changes as each parameter representing the innovation characteristics undergoes a change. The analysis results confirm that relative advantage and compatibility are of critical influence in impacting the threshold and thus the successful market entry. Moreover, the effect size was different depending on the size of the firm's proprietary customer base. Based on the findings, discussion on new product design strategies for companies having different market positions (i.e., new start-up firms, established firms, and incumbent market leaders) is provided.

While many innovations successfully enter the market, take off, and make full diffusion, others diffuse only partially and then perish. As an attempt to explain the successful versus failed market penetration, the so-called “threshold model” has garnered much attention in both academic and business realms Barabasi, 2002, Geroski, 2000, Goldenberg et al., 2000, Golder & Tellis, 1997, Haldar & Rao, 1998 and Rogers, 1995. In his seminal book, Rogers (1995, p. 313) asserted that A crucial concept in understanding the social nature of the diffusion process is the critical mass, a point in the process when diffusion becomes self-sustaining. A network scientist Barabasi (2002, p. 131) also mentioned that Recognizing that passing a critical threshold is the prerequisite for the spread of fads and viruses was probably the most important conceptual advance in understanding spreading and diffusion. In this article, we try to contribute to the understanding of how the design characteristics of an innovative product impact its penetration success in the market, by characterizing the threshold as depending upon the innovation characteristics. Many adoption models designate the innovation characteristics (i.e., relative advantage, compatibility, complexity, triability, and observability) as a key factor affecting the pattern of market penetration Guiltinan, 1999, Holak & Lehmann, 1990, Rogers, 1995, Souder & Song, 1997, Tornatzky & Klein, 1982 and Waarts et al., 2002. After Holak and Lehmann (1990) provided empirical evidence that relative advantage and compatibility “directly” affect consumers' purchase intention, the two factors have received favoritism in recent published articles in the area of product innovation. Studies by Guiltinan (1999), Plouffe, Vandenbosch, and Hulland (2001), and Waarts et al. (2002) are some of the examples that put special emphasis on the two innovation attributes. The two innovation characteristics are also peculiar in that they are defined in relation to existing products, while others (complexity, trialability, and observability) indicate the innate characteristics of an innovation. Further, popularity of the two “relative” measures suggests that it would be more intuitive to see a new product's market penetration process as the process of building its own base of users in the face of an established network of an incumbent product (Shapiro & Varian, 1999). The present study resorts to an evolutionary game approach in portraying the competition between the old and new products. The purpose of this article is to investigate how an innovative product's competitive characteristics such as relative advantage and compatibility affect the likelihood of its successful market penetration.2 By “successful” market penetration, we mean the innovation making a full market penetration beyond the threshold up to its potential. To do that, we first derive a formula of the threshold for successful market penetration in terms of innovation characteristics. We then examine via numerical analyses how the design characteristics affect the probability distribution of the threshold and, subsequently, the probability of successful market penetration. We conclude with a discussion on the implications about new product design strategies for firms under various market positions.

This study is aimed to analyze how innovation characteristics such as relative advantage and compatibility affect the likelihood of successful market penetration of innovative new products, in the market where consumption externality matters. In the process, we came up with an equation that describes the critical threshold of market acceptance for an innovation to go beyond to make full penetration in the market. Key findings from our numerical analyses are summarized as follows. First, the analysis results confirm that the new product's performance, or the relative advantage, facilitates successful market penetration. However, the effect size was little when the customer base is small, while it greatly increases the success probability when the customer base is large. Second, it turns out that the backward compatibility is helpful in reducing the level of resistance and thus facilitating successful market entry. Unlike performance, however, compatibility enhancement turns out to be more effective when the customer base is relatively small. Third, when forward compatibility of the incumbent product increases, the probability of new product's successful entry drops, and the drop is relatively steeper when the customer base is large. Fourth, our investigation on how consumer heterogeneity affects the penetration leads to the conclusion that, as consumers' perceived benefits from new products are diverse, the uncertainty in both success and failure increases. A practical insight from this finding is that if consumers are heterogeneous in their attitudes, rather conservative marketing strategy is recommended. Otherwise, offensive marketing would be more effective. The comparison of effect sizes also sheds much insight to the managers facing new product design decisions. For example, under the situation of performance/compatibility trade-off, increasing compatibility, relative to performance, appears to be a more effective way for a firm with a small customer base to improve the chance of successful market entry, whereas performance enhancement seems to be more critical when the firm has a substantial customer base. Based on the findings, we also discussed various implications for product managers of companies having different market status (i.e., new start-up firms, established firms, and the incumbent market leaders). Unlike most studies, our model supposes a competitive situation and describes more general occasions, including the case when the innovation stops spreading in the market. In addition, the present model incorporates detailed product characteristics such as performance, and forward and backward compatibilities, thereby yielding useful insights for new product design strategies. The followings are limitations of the current study and suggestions for future research. First, although the model used in the study includes major characteristics of an innovative product, it does not count in marketing variables such as price and advertising. One may consider several alternatives to reflect such marketing effects. One way is to indicate the early customer base as a function of marketing variables. Or, one can model the design parameters to be influenced by the marketing variables. Second, our study performed analytic investigations through numerical simulations instead of providing empirical results. Thus, it is necessary and imminent to verify the findings with real data. Although, it remains as a problem to find objective ways to measure the performance and compatibility of a product and to locate data on products that failed to spread in the market. Verifying any of the findings derived in this study will be of critical value to practitioners. Lastly, one needs to analyze more general models that mitigate the degree of several assumptions of the model, such as the relations of a, b, c, and d. It would be worthwhile to analyze several special cases (e.g., the relationship between complementary goods), as well as more general nonsymmetrical payoff matrix to study the competition of various innovations in their respective markets.