arXiv 2412.069922024-12physics.soc-phphysics.data-an

量化科学、技术、商业和药理学领域中创新弃用动态

Quantifying the Dynamics of Innovation Abandonment Across Scientific, Technological, Commercial, and Pharmacological Domains

Center for Science of Science and Innovation（科学科学与创新研究中心）；Northwestern Institute on Complex Systems (NICO)（西北大学复杂系统研究所）；Kellogg School of Management（凯洛格管理学院）；Centre for Interdisciplinary Methodologies, University of Warwick（华威大学跨学科方法中心）；Department of Physics, University of Miami（迈阿密大学物理系）；Telenor Research and Development（泰伦诺研发部）

Binglu Wang, Ching Jin, Chaoming Song, Johannes Bjelland, Brian Uzzi, Dashun Wang

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AI总结：

本研究通过四个跨领域数据集揭示创新弃用遵循优先弃用模式，即弃用概率随时间及邻居弃用数增加，并分析其对网络结构坍塌的影响，提出分析框架，表明该模式是创新生命周期的普遍属性。

摘要：

尽管关于创新扩散的文献浩如烟海，且其影响涉及广泛学科，但我们对创新弃用的理解仍然有限，而这对更深入地理解创新生命周期至关重要。在此，我们分析了四个大规模数据集，这些数据集捕捉了科学、技术、商业和药理学领域中创新弃用的时间与结构模式。本文做出三项主要贡献。首先，在这些不同领域中，我们发现了一种简单的优先弃用模式，即个体或组织弃用一项创新的概率随时间增加，并与已弃用该创新的网络邻居数量相关。其次，我们发现优先弃用的存在从根本上改变了底层生态系统崩溃的方式，在网络系统中诱发了一种新颖的结构性坍塌，而这类系统通常被认为对弃用具有鲁棒性。第三，我们推导出一个分析框架，以系统性地理解优先弃用对网络动力学的影响，并指出在特定条件下，与随机弃用相比，它可能加速、减速或产生相同效果，这取决于网络拓扑结构。总之，这些结果加深了我们对网络化社会系统中创新弃用的定量理解，对创新社区的鲁棒性和运作具有启示意义。总体而言，它们表明创新弃用的动态遵循简单且可复现的模式，暗示所揭示的优先弃用可能是创新生命周期的一个普遍属性。

英文摘要：

Despite the vast literature on the diffusion of innovations that impacts a broad range of disciplines, our understanding of the abandonment of innovations remains limited yet is essential for a deeper understanding of the innovation lifecycle. Here, we analyze four large-scale datasets that capture the temporal and structural patterns of innovation abandonment across scientific, technological, commercial, and pharmacological domains. The paper makes three primary contributions. First, across these diverse domains, we uncover one simple pattern of preferential abandonment, whereby the probability for individuals or organizations to abandon an innovation increases with time and correlates with the number of network neighbors who have abandoned the innovation. Second, we find that the presence of preferential abandonment fundamentally alters the way in which the underlying ecosystem breaks down, inducing a novel structural collapse in networked systems commonly perceived as robust against abandonments. Third, we derive an analytical framework to systematically understand the impact of preferential abandonment on network dynamics, pinpointing specific conditions where it may accelerate, decelerate, or have an identical effect compared to random abandonment, depending on the network topology. Together, these results deepen our quantitative understanding of the abandonment of innovation within networked social systems, with implications for the robustness and functioning of innovation communities. Overall, they demonstrate that the dynamics of innovation abandonment follow simple yet reproducible patterns, suggesting that the uncovered preferential abandonment may be a generic property of the innovation lifecycle.

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