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61.
Complementarities between technological and non-technological innovation are crucial determinants of firm performance. Although innovation complementarity has been extensively tested in the empirical literature, it has not been analysed in conjunction with innovation persistence. This fact is mainly due to the lack of data sets able to provide adequate longitudinal information. The capacities to develop market-oriented behaviour and introduce new organisational innovations, together with technological innovation, are the drivers of a firm’s productivity and profitability. We find that these activities complement technological innovation and that their impact is greater when they persist over time, thus introducing a more general concept of innovation persistence. We present an empirical model based on a large new panel of Italian manufacturing firms covering the period 2000–2012 which enables us to determine the precise impacts of a firm’s innovative attitude, in a broad definition that incorporates non-technological innovation and persistence, on its productivity and profitability. 相似文献
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In the field of smart communities, significant progress has been made in recent years. The objective of constructing smart communities is to improve the quality of life of their inhabitants. To accomplish this objective, technologies such as Internet of Things (IoT) and Artificial Intelligence (AI) were deployed. The data gathered and processed by IoT devices, particularly those with centralized control, are however susceptible to availability, integrity, and privacy risks. Due to its inherent properties of transparency, immutability, and underlying secure-by-design architecture, Distributed Ledger Technology (DLT) and Smart Contracts enable distributed, decentralized, automated workflows that can be incorporated to automate the management of the next generation of IoT networks. Using a potential use case, a conceptual architecture for securing smart communities with DLT is developed and explained. In this paper, a framework for IoT eco-systems is proposed that provides seamless integration between IoT and DLT to create a decentralized trusted architecture that ensures the trustworthiness of IoT eco-systems at design time and a trust reputation model based on the architecture to protect it at run-time. In addition, the initial implementation steps are described for this framework. 相似文献
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When students use computers as learning tools, the whole process of learning, and, indeed, the learners themselves, are transformed. This article illustrates some techniques that foster transformative learning in computer-assisted first-year literature classes: first, a lesson plan on A Valediction: Forbidding Mourning that uses Microsoft Word functions, including format painter, tables, and annotation to explore meaning in context; second, a plan for learners to use subconference options in the Daedalus Interactive Writing Environment to analyze Oedipus Rex; finally, a demonstration of how students engage in a meta-reflection process as they explore Barn Burning with Freelance Graphics.Marguerite Jamieson is an English instructor at Anne Arundel Community College in Arnold, Maryland, and a doctoral student at George Mason University. Her research interests include forming bridges between adult learning theory and contemporary literary theory — especially drawing on transformational learning theory and the work of Mikhail Bakhtin and Lev Vygotsky.Rebecca Kajs holds a doctorate in English from Texas Woman's University with a concentration in rhetoric. For ten years, she taught the use of heuristic tools for reading analysis at the University of Texas at Arlington. She is currently an associate professor of English and Philosophy at Anne Arundel Community College.Anne Agee holds a doctorate in rhetoric from The Catholic University of America. A professor of English and formerly director of the Humanities Computer Center at Anne Arundel Community College, she is currently the college's Coordinator of Instructional Technology. Dr. Agee and Professor Jamieson have collaborated in a study of the learning environment in a computer classroom, the results of which were published in the Fall 1995 issue of Teaching/Learning Conversations. Dr. Agee has also published Using [Daedalus] InterChange as a Teachers' Journal in the Fall 1995 issue of Wings. 相似文献
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社团结构是反映复杂网络整体性质的重要特征,本文从强社团结构定义出发提出简单启发式强社团结构探测算法,受启发因素为度-度负相关性和簇-度负相关性.利用该算法对空手道俱乐部成员关系网络和美国大学橄榄球队网络进行社团结构探测,验证了该算法能正确探测出网络的强社团结构.并将划分结果与传统划分进行比较分析,该算法未引入其它量化指标或中间变量,降低了计算复杂度,在采用方法上不同于单纯的分裂或聚合,有效地提高了探测速度,更适合大规模复杂网络社团结构探测. 相似文献
65.
Examining knowledge contribution from the perspective of an online identity in blogging communities 总被引:1,自引:0,他引:1
Knowledge contribution is one of the essential factors behind the success of blogging communities (BCs). This research studies knowledge contribution behavior in a BC from the perspective of knowledge contributors and their characteristics using the lens of social identity theory. Social identity theory asserts that individuals are fundamentally motivated to present or communicate their identities in everyday social life through behavior. A similar line of reasoning can be used to argue that members of a BC would also be motivated to communicate their online identities through their behavior, that is, through knowledge contribution in the BC. Specifically, this study conceptualized the online identity and examined the effects of its personal (online kindness, online social skills, and online creativity) and social aspects (BC involvement) on knowledge contribution. The data was collected using an online survey from the members of Cyworld, a popular BC in South Korea and a few other countries (members from South Korea were included in this study). The results indicate that both the personal and social aspects of online identity and their interactions significantly influenced knowledge contribution. Based on the findings, this study offers suggestions to organizers of BCs to enhance the knowledge contribution from their members. 相似文献
66.
基于权重信息挖掘社会网络中的隐含社团 总被引:1,自引:0,他引:1
社团结构是一种普遍存在于各类真实网络中的结构特性.挖掘网络的社团结构对于理解网络的功能与行为有着重要作用.然而,现有的各种社团挖掘算法仅仅基于网络拓扑结构信息,而忽视了蕴涵于真实社会网络边权信息中丰富的语义信息.目前普遍使用的基于模块性最大化的社团挖掘算法倾向于将小社团合并,这使得语义上丰富的小社团容易湮灭于基于拓扑结构信息所挖掘出的大社团中.而挖掘出这些隐含于大社团中的有着丰富语义内涵的小社团对于加深社会网络语义层面的理解有着重要作用.为此,提出一个接近线性复杂度的有权网络社团挖掘算法.通过充分利用权重信息,算法可以将社会网络划分为富含语义信息的粒度较细且相对较小的隐含社团.通过对基于DBLP作者合作网络的实证分析,证实了新算法的有效性和高效性. 相似文献
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处理海量级数据的有效途径之一是将算法分解为一系列互不依赖的任务,然后利用开源工具并行地执行算法。而在重叠社区发现算法中,基于局部拓展的方法在拓展阶段往往仅需要局部社区及其相应的邻居结点的信息,因而具备可并行执行的可能性。提出了一种可并行化执行的局部拓展算法,并借助开源工具Spark将其实现。算法分为4个阶段。首先,挑选出一组不相关的中心结点并使用其对应的局部网络作为种子;其次,通过删除本身连接不是很紧密的局部网络来过滤选出的种子;然后,采用一种批量式的拓展策略来拓展种子,即一次向局部社区中添加一批邻居结点或从社区中删除一批结点;最后,融合相似的社区。在人工生成的网络以及真实世界中的网络上的实验结果显示 ,所提算法既准确又高效。 相似文献