| Innovation diffusion of new products draws extant interests in the fields of technological innovation, marketing and management science. With the high pace growth of launch of new products, decision makers need to pay much attention to how to push these new products into market successfully. However, for different types of new products, it is still in need of answers that whether influential factors are different. In the study of innovation diffusion of new products, prior researchers still focus on the impact of interpersonal relationship and contextual variables on new products diffusion, rather than studying before categorizing products.Hence, based on Bass Model and from the perspective of products complexity, this study tries to answer these core questions:which factors of demand side have different impact on innovation diffusion along with the changing of products complexity? And among them, which factors have stronger effect on diffusion with higher product complexity? In order to answer these questions, this study answers the influence of three factors of demand side (opinion leaders, network externality, repetitive purchase) on innovation diffusion under different products complexities through three sub-studies, respectively:Sub-study One examines the direct influence of products complexity on innovation diffusion, and the joint influence of opinion leaders and products complexity on innovation diffusion. Via advancing the model developed by Van Eck, Jager and Leeflang (2011),I come up with three dyads of comparison models, use net logo simulation analysis and SPSS statistics analysis, and analyze the direct and joint effect of opinion leaders and products complexity on innovation diffusion.Sub-study Two studies whether overall network externality has impact on potential adopters’decision when partial network externality and public praise effect exist. After advancing the model in the Sub-study One. I use net logo simulation analysis and SPSS statistics analysis to examine the direct and joint effect of overall network externality on innovation diffusion and study the relationship of these effects and network structure (small world model and scale-free network).Sub-study Three studies the effect of repetitive purchase (purchasing repetitively or not, the depth of repetitive purchase) and products complexity’on innovation diffusion. Through improving the model from Sub-study One. I come up with three dyads of comparison models, and use net logo and SPSS to analyze the effect mentioned above. I also study the impact of negative public praise on this result.After a series of studies, main conclusions are following:(1) Opinion leaders has significantly positive effect on the scale and speed of innovation diffusion, but this effect will decline with the decrease of products complexity. Besides, products complexity has significantly negative effect on the scale of innovation diffusion, but products complexity has significantly positive effect on the speed of diffusion in ordinary users when opinion leaders exist.(2) Overall network externality has significantly positive influence on innovation diffusion, but this influence will decline with the decrease of products complexity. However, overall network externality yields different influences on the speed of diffusion along with the changing of network structure.(3) Repetitive purchase has significantly positive impact on both speed and scale of innovation diffusion. But with the climbing of products complexity, repetitive purchase has stronger impact on the scale of diffusion, while the impact on speed will be weaker.(4) Depth of repetitive purchase has no significant impact on scale of diffusion. It has different impact on the speed when faced with different degree of negative public praise.To sum up, this study has several contributions to innovation diffusion research:(1) The relationship between products complexity and innovation diffusion is not easily negative.According to sub-study One, when opinion leaders exist, with the increase of products complexity, diffusion will be faster. So, products complexity is not necessarily negative related with the speed of diffusion. When some factors (e.g. Opinion leaders) don’t have very strong influence on the speed of diffusion, products complexity is not necessarily negative related to the speed of diffusion.(2) Opinion leaders’s effect on diffusion changes with the change of products complexity.In accordance with sub-study One, opinion leaders are significantly positive related to the scale and speed of innovation diffusion, however, this kind of relationship will decrease when products complexity declines. When products complexity is high, opinion leaders has positive influence on both scale and speed of innovation diffusion. When products complexity is low, the gap between opinion leaders and ordinary users is narrower, which leads to weaken the influence of opinion leaders on diffusion. However, at this time, users who are more easily to be influenced at the early time of diffusion are more important to innovation diffusion. Hence, to a certain degree, from the perspective of products complexity, this study explains the differences about opinion leaders’effect on innovation diffusion.(3) Overall network externality has significant impact on innovation diffusion. and this impact will be more significant when products complexity is high and when located in network structure with small world model.According to Sub-study Two, when considering consumers, it is not exhaustive that prior studies only care about overall network externality or partial one. From this study, no matter under the structure of scale-free network or small world model, overall network externality has significant impact on innovation diffusion when partial network externality exists, and this impact will be stronger along with the climbing of products complexity. As a result, this study thinks that for potential adopters, overall network externality is still significantly related to diffusion, although when products complexity is low, this impact is very weak. After this study, we find that network structure has significant influence on diffusion in deed. Under different network structure, overall network externality has different effects on the speed of innovation diffusion, and under different products complexity, when potential adopters have different network structures, maybe overall network externality can’t accelerate the increase of the speed of diffusion.(4) This study comes up with a simulation model of repetitive purchase and extends the study of repetitive purchase context and innovation diffusion.This study uses the analysis method based on intellectual simulation, builds a simulation model of repetitive purchase, and studies the relationship between repetitive purchase and innovation diffusion, together with the effect of negative public praise. We find that repetitive purchase plays an important role in innovation diffusion, which is consistent with prior researches. The depth of repetitive purchase will lead to the increase of innovation diffusion speed, rather than the scale. Hence, this study provides some assistance for the setting of prediction model parameters. If the independent variable of prediction model is the sales amount of new products, the design of parameters of the depth of repetitive purchase is very important. But when the independent variable is the diffusion scale of new products, the design of parameters of depth may be not that important. This study also takes the relationship of repetitive purchase and the speed of diffusion into consideration. Under the influence of products complexity and negative public praise, this relationship presents a complicated non-linear curve, which needs further study and analysis. |
PDF Full Text Request