应用产品创新速度与用户评论之间的动态关系

Dynamic Relationship between Application Innovation Speed and Customer Reviews

近年来应用产品行业发展迅速,同时也面临着市场竞争严峻、营销经费有限和技术成本高昂等挑战,因此,应用行业大多采用快速更新的方法对产品进行创新,这样做的好处是有助于开发商基于海量用户反馈对产品进行持续迭代。其中,应用产品创新速度的问题引起了学界的关注,已有研究聚焦创新速度对结果变量的单向影响,较少对创新速度与创新效果之间的动态性和迭代性展开系统的探讨。从组织学习和用户行为动机视角,详细分析应用产品创新速度与用户评论的相互影响机制,结合不同的应用类型拓展研究结论的边界性。获取924个应用产品的版本更新数据集,采用面板向量自回归模型,研究应用产品创新速度与用户评论数量和评分在应用产品创新过程中的动态迭代关系;基于不同类型产品所对应用户知识的差异性,以及用户对不同类型产品需求决策机制的差异性,分析应用产品类型对应用产品创新速度与用户评论之间关系的影响。研究结果表明,(1)应用产品创新速度与用户评论数量和评分之间存在普遍的协同增强关系,即应用产品创新速度正向影响用户评论数量和评分,用户评论数量和评分也反过来促进应用产品创新速度;(2)持续更新过程中,应用产品的用户评论数量与评分之间也存在协同增强关系,并且应用产品创新速度、评论数量、评分存在动态滞后效应;(3)对于享乐型应用,协同增强的动态迭代关系并不成立,应用产品创新速度对评论数量和评分无显著影响,评分反而负向影响应用产品创新速度。理论上,界定了应用产品创新模式中相关变量之间的动态迭代效应,比较了该效应在不同类型应用产品之间的差异;实践上,指导应用行业基于不同类型的应用产品、依据不同的用户评论特质和用户评分信号对应用产品进行更新迭代,帮助应用产品开发商实现持续创新。

The application(app)industry has faced multiple challenges while developing rapidly in recent years,such as the competitive marketing environment,limited marketing budgets,and high research and development costs.As a result,app developers mostly take an agile innovation model with rapid updates in the product development process,which helps developers iterate continuously according to the mass customer feedbacks.Among relevant studies,speed of innovation has triggered the attention of academic circles,but existing research focuses on the one-way influence of innovation speed on the outcomes.While the dynamic and iterative nature of the relationships between innovation speed and its results are seldomly considered systematically.The current study attempts to examine the dynamic relationship between the innovation speed and customer reviews.And we further discuss the boundary of the dynamic relationship by considering different app types.To answer the above questions,the authors discussed in detail the interactive mechanism of innovation speed of apps and customer reviews from perspectives of organizational learning and customer behavioral motivation.Following the theoretical analysis,we obtained a version update dataset of 924 apps.By using a method of panel vector autoregressive model(PVAR),the author analyzed the dynamics of app innovation speed and review volume and ratings during the innovation process.Furthermore,we also examine the impact of product type on the relationship between innovation speed and customer reviews for the difference in customer knowledge of firm′s learning and the difference in customer decision-making mechanism brings by different types of products.The results show that:(1)there is a general synergistic reinforcement relationship between the app innovation speed and the volume and rating of customer reviews—that is,the innovation speed of apps will positively affect the volume and rating of customer reviews,and the volume and rating of customer reviews will,in turn,promote the app innovation speed;(2)there is also a synergistic reinforcement relationship between the review volume and the review rating in the continuous updating process.Additionally,hysteresis effects are found on the innovation speed,the volume of product reviews,and the rating of reviews respectively;(3)the synergistically reinforced dynamic iterative relationship does not hold for all conditions.For example,for hedonic apps,the innovation speed exerts no significant effect on neither review volumes nor ratings,on the contrary,the innovation speed will be negatively affected by product ratings.These findings provide abundant theoretical and practical contributions.Theoretically,the authors not only illustrate the"dynamic and iterative"relationship among the focal variables in the app innovation model but also compare the differences of the former relationships on key product types.Managerially,this paper guides the application enterprises to practice a rapid innovation model according to different types of products,characteristics of reviews,and rating signals during the app innovation,helping developers to achieve continuous innovation.