基于产品复杂性视角的新产品创新扩散研究
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摘要
新产品创新扩散无论在创新领域、市场营销领域还是管理科学领域都是一个被广泛关注的问题。随着新产品的推出越来越多,如何把这些新产品成功的推向市场是每一个市场策略制定者关注的重点。然而,对于不同类型的新产品,影响它们成功推广的因素是否存在不同仍然有待回答。在新产品创新扩散领域的研究中,现有的研究关注的重点仍然是人际间关系与情境变量对新产品扩散的影响,而很少区分不同的产品类别来研究上述影响因素对新产品扩散影响的不同。
因此,本研究将基于产品复杂性的视角试图回答一个核心问题：基于Bass模型拓展的需求方影响因素是否会随着产品复杂性的不同而对新产品创新扩散有不同影响,并且识别哪些因素对产品复杂性高的产品的扩散影响更大?为了回答上述问题,本研究通过三个子研究分别回答三个需求方因素(意见领袖、网络外部性、重复购买行为)在产品复杂性不同的情境下对新产品创新扩散的影响：
子研究一首先研究了产品复杂性对新产品创新扩散的直接影响,并结合意见领袖研究了意见领袖和产品复杂性对新产品创新扩散的交互影响。通过改进van Eck、Jager和Leeflang(2011)的模型,提出了3组对比模型,运用netlogo仿真分析和SPSS统计分析,分析了意见领袖和产品复杂性对新产品创新扩散的直接影响和交互影响。
子研究二结合产品复杂性研究了全局网络效应在局部网络效应和口碑效应存在的同时是否对潜在采纳者的采纳决策存在影响。通过改进子研究一的模型,运用netlogo仿真分析和SPSS统计方法分析了全局网络效应和产品复杂性对新产品创新扩散的直接影响和交互影响,并且分析了这些作用与网络结构(小世界模型和无标度网络)之间的关系。
子研究三研究了重复购买行为(有无重复购买和重复购买深度)与产品复杂性对新产品创新扩散的影响。通过改进子研究一的模型,提出了3组对比模型,并运用netlogo仿真分析和SPSS统计方法分析了上述影响,此外还讨论了负面口碑强度的变化对上述结果的影响。
通过上述研究,得到以下主要结论：
(1)意见领袖对新产品创新扩散的扩散规模和扩散速度有显著正向影响,但是这种影响会随着产品复杂性的降低而减弱。此外,产品复杂性对新产品创新扩散的扩散规模有显著负向影响；但是当群体中存在意见领袖时,产品复杂性对对普通用户的新产品扩散速度有显著正向影响。
(2)全局网络效应对新产品创新扩散的扩散规模存在显著正向影响,但是这种影响会随着产品复杂性的降低而减弱。此外,全局网络效应对新产品创新扩散的扩散速度的影响会随着网络结构的不同而不同。
(3)重复购买行为对新产品创新扩散的扩散速度和扩散规模都具有显著正向影响,并且随着产品复杂性的提高,重复购买行为对新产品的扩散规模的影响逐渐增强,但是对于新产品创新扩散的扩散影响会逐渐减弱。
(4)重复购买深度对新产品创新扩散的扩散规模没有显著影响,对新产品的扩散速度的影响会随着负面口碑强度的不同而不同。
根据本文的研究,对新产品创新扩散领域主要进行了以下拓展和深化：
(1)产品复杂性对新产品创新扩散的扩散速度并不是简单的负向影响的关系。
通过本研究的子研究一发现,在意见领袖存在的时候,随着产品复杂性的提高,新产品的扩散速度在普通用户中是逐渐加快的。因此,产品复杂性对新产品创新扩散速度的总效应并不一定是负向关系。当有些因素(比如意见领袖)对新产品创新扩散的速度交互作用影响很大时,产品复杂性对扩散速度的总效应并不总是呈现负向关系,这也给产品复杂性对感知有用性研究的分歧提供了一个新的解释视角。
(2)意见领袖对新产品创新扩散的影响随着产品复杂性的提高而增强。
通过本研究的子研究一发现,意见领袖对新产品的扩散规模和扩散速度都具有显著的正向影响,但是这种影响随着产品复杂性的降低而减弱。当产品复杂性高时,意见领袖无论是对新产品的扩散规模还是扩散速度都有显著影响；然而,当产品复杂性低时,意见领袖与普通用户的差距缩小,意见领袖对新产品创新扩散的影响降低,而这时在扩散初期更易受影响的用户对新产品创新扩散的影响会更加重要。因此,本研究通过产品复杂性的视角在一定程度上解释了关于意见领袖对新产品创新扩散的影响的分歧。
(3)全局网络效应对新产品创新扩散具有显著影响,并且这种影响在产品复杂性高并基于小世界模型的网络结构下更为显著。
通过本研究的子研究二发现,以往的研究中在消费者方面只考虑全局网络效应或局部网络效应是不全面的。通过本研究发现,无论是在无标度网络结构下还是在小世界模型的网络结构下,全局网络效应在局部网络效应存在的基础上都会对新产品的扩散规模产生显著正向影响,而且这种作用会随着产品复杂性的提高而加强。因此,本研究认为对于潜在采纳者,全局网络效应仍然会对新产品的扩散规模产生显著影响,虽然在产品复杂性低时影响非常微弱。通过本研究发现,网络结构对新产品的扩散速度确实存在显著影响。在不同的网络结构下,全局网络效应对新产品的扩散速度的影响会有不同,并且根据产品复杂性的不同,当潜在采纳者具有不同的网络结构时全局网络效应可能并不能促进扩散速度的增加。
(4)提出了重复购买的仿真模型,并拓展了重复购买情境对新产品创新扩散的影响研究。
本研究应用基于智能体仿真研究方法,建立了重复购买的仿真模型,并加入了负面口碑的作用,研究了重复购买与新产品创新扩散的关系。通过本研究发现,与以往对重复购买的研究者一致,重复购买在新产品创新扩散过程中确实发挥着重要的作用。重复购买行为或多数量采纳确实对新产品的采纳规模和采纳速度有重要影响,但是重复购买深度并不会促进新产品的扩散规模的增加,而是对新产品的销售额的增加更为有用。因此,通过本研究可以为预测模型的参数设定提供一些帮助。如果预测模型的因变量是新产品的销售额,那么重复购买深度的参数设定有很大影响,但是如果因变量是新产品的扩散规模,那么重复购买深度的参数对因变量的影响可能不会非常重要。本研究还研究了重复购买与新产品创新扩散速度影响,通过研究发现在产品复杂性和负向口碑的影响下,两者间的关系呈现了复杂的非线性关系,后续对重复购买与新产品创新扩散速度之间的关系还需要更进一步的分析和研究。
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.
因此,本研究将基于产品复杂性的视角试图回答一个核心问题：基于Bass模型拓展的需求方影响因素是否会随着产品复杂性的不同而对新产品创新扩散有不同影响,并且识别哪些因素对产品复杂性高的产品的扩散影响更大?为了回答上述问题,本研究通过三个子研究分别回答三个需求方因素(意见领袖、网络外部性、重复购买行为)在产品复杂性不同的情境下对新产品创新扩散的影响：
子研究一首先研究了产品复杂性对新产品创新扩散的直接影响,并结合意见领袖研究了意见领袖和产品复杂性对新产品创新扩散的交互影响。通过改进van Eck、Jager和Leeflang(2011)的模型,提出了3组对比模型,运用netlogo仿真分析和SPSS统计分析,分析了意见领袖和产品复杂性对新产品创新扩散的直接影响和交互影响。
子研究二结合产品复杂性研究了全局网络效应在局部网络效应和口碑效应存在的同时是否对潜在采纳者的采纳决策存在影响。通过改进子研究一的模型,运用netlogo仿真分析和SPSS统计方法分析了全局网络效应和产品复杂性对新产品创新扩散的直接影响和交互影响,并且分析了这些作用与网络结构(小世界模型和无标度网络)之间的关系。
子研究三研究了重复购买行为(有无重复购买和重复购买深度)与产品复杂性对新产品创新扩散的影响。通过改进子研究一的模型,提出了3组对比模型,并运用netlogo仿真分析和SPSS统计方法分析了上述影响,此外还讨论了负面口碑强度的变化对上述结果的影响。
通过上述研究,得到以下主要结论：
(1)意见领袖对新产品创新扩散的扩散规模和扩散速度有显著正向影响,但是这种影响会随着产品复杂性的降低而减弱。此外,产品复杂性对新产品创新扩散的扩散规模有显著负向影响；但是当群体中存在意见领袖时,产品复杂性对对普通用户的新产品扩散速度有显著正向影响。
(2)全局网络效应对新产品创新扩散的扩散规模存在显著正向影响,但是这种影响会随着产品复杂性的降低而减弱。此外,全局网络效应对新产品创新扩散的扩散速度的影响会随着网络结构的不同而不同。
(3)重复购买行为对新产品创新扩散的扩散速度和扩散规模都具有显著正向影响,并且随着产品复杂性的提高,重复购买行为对新产品的扩散规模的影响逐渐增强,但是对于新产品创新扩散的扩散影响会逐渐减弱。
(4)重复购买深度对新产品创新扩散的扩散规模没有显著影响,对新产品的扩散速度的影响会随着负面口碑强度的不同而不同。
根据本文的研究,对新产品创新扩散领域主要进行了以下拓展和深化：
(1)产品复杂性对新产品创新扩散的扩散速度并不是简单的负向影响的关系。
通过本研究的子研究一发现,在意见领袖存在的时候,随着产品复杂性的提高,新产品的扩散速度在普通用户中是逐渐加快的。因此,产品复杂性对新产品创新扩散速度的总效应并不一定是负向关系。当有些因素(比如意见领袖)对新产品创新扩散的速度交互作用影响很大时,产品复杂性对扩散速度的总效应并不总是呈现负向关系,这也给产品复杂性对感知有用性研究的分歧提供了一个新的解释视角。
(2)意见领袖对新产品创新扩散的影响随着产品复杂性的提高而增强。
通过本研究的子研究一发现,意见领袖对新产品的扩散规模和扩散速度都具有显著的正向影响,但是这种影响随着产品复杂性的降低而减弱。当产品复杂性高时,意见领袖无论是对新产品的扩散规模还是扩散速度都有显著影响；然而,当产品复杂性低时,意见领袖与普通用户的差距缩小,意见领袖对新产品创新扩散的影响降低,而这时在扩散初期更易受影响的用户对新产品创新扩散的影响会更加重要。因此,本研究通过产品复杂性的视角在一定程度上解释了关于意见领袖对新产品创新扩散的影响的分歧。
(3)全局网络效应对新产品创新扩散具有显著影响,并且这种影响在产品复杂性高并基于小世界模型的网络结构下更为显著。
通过本研究的子研究二发现,以往的研究中在消费者方面只考虑全局网络效应或局部网络效应是不全面的。通过本研究发现,无论是在无标度网络结构下还是在小世界模型的网络结构下,全局网络效应在局部网络效应存在的基础上都会对新产品的扩散规模产生显著正向影响,而且这种作用会随着产品复杂性的提高而加强。因此,本研究认为对于潜在采纳者,全局网络效应仍然会对新产品的扩散规模产生显著影响,虽然在产品复杂性低时影响非常微弱。通过本研究发现,网络结构对新产品的扩散速度确实存在显著影响。在不同的网络结构下,全局网络效应对新产品的扩散速度的影响会有不同,并且根据产品复杂性的不同,当潜在采纳者具有不同的网络结构时全局网络效应可能并不能促进扩散速度的增加。
(4)提出了重复购买的仿真模型,并拓展了重复购买情境对新产品创新扩散的影响研究。
本研究应用基于智能体仿真研究方法,建立了重复购买的仿真模型,并加入了负面口碑的作用,研究了重复购买与新产品创新扩散的关系。通过本研究发现,与以往对重复购买的研究者一致,重复购买在新产品创新扩散过程中确实发挥着重要的作用。重复购买行为或多数量采纳确实对新产品的采纳规模和采纳速度有重要影响,但是重复购买深度并不会促进新产品的扩散规模的增加,而是对新产品的销售额的增加更为有用。因此,通过本研究可以为预测模型的参数设定提供一些帮助。如果预测模型的因变量是新产品的销售额,那么重复购买深度的参数设定有很大影响,但是如果因变量是新产品的扩散规模,那么重复购买深度的参数对因变量的影响可能不会非常重要。本研究还研究了重复购买与新产品创新扩散速度影响,通过研究发现在产品复杂性和负向口碑的影响下,两者间的关系呈现了复杂的非线性关系,后续对重复购买与新产品创新扩散速度之间的关系还需要更进一步的分析和研究。
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.
引文
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