当前位置:
X-MOL 学术
›
J. Account. Econ.
›
论文详情
Our official English website, www.x-mol.net, welcomes your
feedback! (Note: you will need to create a separate account there.)
Accounting and innovation: Paths forward for research
Journal of Accounting and Economics ( IF 5.4 ) Pub Date : 2024-08-08 , DOI: 10.1016/j.jacceco.2024.101733 Mary E. Barth , Kurt H. Gee
Journal of Accounting and Economics ( IF 5.4 ) Pub Date : 2024-08-08 , DOI: 10.1016/j.jacceco.2024.101733 Mary E. Barth , Kurt H. Gee
Glaeser and Lang (2024; GL) reviews the accounting literature on innovation, which has increased substantially in recent years. GL makes an important contribution to accounting research by bringing into the literature the implications of Romer's Nobel Prize winning endogenous growth theory and by explaining how accounting research addresses questions related to innovation. We contribute to accounting research by building on GL's foundation to suggest three main paths forward for future innovation research. First, focus on innovation's three defining attributes: novelty, nonrivalry, and partial excludability. Second, determine the needs of various users of information about a firm's innovation activities and how to meet those needs; we focus on the needs of investors. Third, address questions our discussion highlights as potentially important for future research on financial reporting and innovation, including the crucial question of an innovation's identifiability.
中文翻译:
会计与创新:研究的前进道路
Glaeser 和 Lang (2024;GL) 回顾了近年来大幅增加的创新会计文献。GL 通过将罗默获得诺贝尔奖的内生增长理论的含义带入文献,并解释会计研究如何解决与创新相关的问题,为会计研究做出了重要贡献。我们以 GL 为基础,为未来的创新研究提出三条主要前进的道路,从而为会计研究做出贡献。首先,关注创新的三个定义属性:新颖性、非竞争性和部分排他性。其次,确定有关公司创新活动的信息的各种用户的需求以及如何满足这些需求;我们专注于投资者的需求。第三,解决我们讨论强调的对未来财务报告和创新研究可能具有重要意义的问题,包括创新可识别性的关键问题。
更新日期:2024-08-08
中文翻译:
会计与创新:研究的前进道路
Glaeser 和 Lang (2024;GL) 回顾了近年来大幅增加的创新会计文献。GL 通过将罗默获得诺贝尔奖的内生增长理论的含义带入文献,并解释会计研究如何解决与创新相关的问题,为会计研究做出了重要贡献。我们以 GL 为基础,为未来的创新研究提出三条主要前进的道路,从而为会计研究做出贡献。首先,关注创新的三个定义属性:新颖性、非竞争性和部分排他性。其次,确定有关公司创新活动的信息的各种用户的需求以及如何满足这些需求;我们专注于投资者的需求。第三,解决我们讨论强调的对未来财务报告和创新研究可能具有重要意义的问题,包括创新可识别性的关键问题。