Knowledge Flow Analysis for Security Protocols

Knowledge flow analysis offers a simple and flexible way to find flaws in security protocols. A protocol is described by a collection of rules constraining the propagation of knowledge amongst principals. Because this characterization corresponds closely to informal descriptions of protocols, it allows a succinct and natural formalization; because it abstracts away message ordering, and handles communications between principals and applications of cryptographic primitives uniformly, it is readily represented in a standard logic. A generic framework in the Alloy modelling language is presented, and instantiated for two standard protocols, and a new key management scheme.Comment: 20 page

Patent Citations and International Knowledge Flow: The Cases of Korea and Taiwan

This paper examines patterns of knowledge diffusion from US and Japan to Korea and Taiwan using patent citations as an indicator of knowledge flow. We estimate a knowledge diffusion model using a data set of all patents granted in the U.S. to inventors residing in these four countries. Explicitly modeling the roles of technology proximity and knowledge decay and knowledge diffusion over time, we have found that knowledge diffusion from US and Japan to Korea and Taiwan exhibits quite different patterns. It is much more likely for Korean patents to cite Japanese patents than US patents, whereas Taiwanese inventors tend to learn evenly from both US and Japanese inventors. The frequency of a Korean patent citing a Japanese patent is almost twice that of the frequency of a Taiwanese patent citing a Japanese patent. We also find that a patent is much more likely to cite a patent from its own technological field than from another field.

How does knowledge flow in organisations?

People are more likely to share information with colleagues inside their professional group, writes Stefano Tassell

Multidimensional Knowledge Flow Dynamics in Context

Knowledge is a sustainable advantage and knowledge assets can increase value with use. A snowball effect of knowledge advantage advocates effective knowledge management and fosters its continual growth as it flows. Knowledge, however, flows unevenly throughout an organization and the problem is that the fundamental dynamics of these flows are still not well characterized in theoretical and computational models. This study built on existing work—knowledge-flow theory, need knowledge generation, and the critical success factors for enterprise resource planning implementation—to examine the multidimensional knowledge-flow phenomenon in context, and used the case study methodology for knowledge-flow theory building. The research question was two-pronged: how can need knowledge and its flow across stakeholders within an organization be explained using a multidimensional knowledge-flow model and how can Nissen’s five-dimensional knowledge-flow model be validated using a real-life immersion case? The researcher relied on three sources of evidence for this case study: project-related documentation, archival records, and interviews. Data triangulation yielded three results components: (a) a chronology of key events that obstructed knowledge flow, (b) a logic model depicting themes that contributed to knowledge-flow obstruction, and (c) explanations of the knowledge-flow patterns. This case study suggested enabling need knowledge determinants and obstructing conditions are in play that determine the path of need knowledge flow. These two research artifacts should be considered together to provide a fresh research avenue towards better understanding of knowledge flow dynamics

Infosys Technologies: Improving Organizational Knowledge Flow

Nandan Nilekani, the chief executive officer (CEO) of Infosys Technologies (Infosys), sat at his desk at the company’s headquarters in Bangalore, India, reading an email from one of his account managers in his North American operations. The manager, Vivek Pradhan, had just landed a project with a major Detroit automobile manufacturer, and was commenting to Nandan on how instrumental the company’s knowledge management (KM) program was in his securing the project. Vivek told Nandan that his client had given him 48 hours to develop a pre-proposal on upgrading its nationwide sales and order operations. He added that his technical team had never seen such a project. Vivek felt he could never meet his pre-proposal deadline, but that evening he received an email from Nandan announcing the launch of a new Domain Competency Group (DCG) as part of the company’s nascent knowledge management (KM) initiative. As stated in the email: DCG would serve as a centralized think-tank to provide round-the-clock knowledge support on various industrial domains to our practice units around the world. Vivek further explained that a quick call to the DCG contact number helped him locate a similar project completed for a German automotive company. He was sent the necessary materials, including a client presentation, which proved very similar to what his client had in mind. After reading the email, Nandan sat back in his chair feeling quite pleased at the success of the five-year-old KM program. Infosys’ KM implementation was guided by the KM Maturity Model (KMM) (see Exhibit 1). 2 Infosys was currently working towards attaining the fourth level of KM maturity. However, one requirement was seriously lacking and would impede progress to the next level: Infosys did not have robust metrics for assessing productivity benefits of the KM program

Knowledge flow across inter-firm networks: the influence of network resources, spatial proximity, and firm size

The objective of this paper is to analyze the characteristics and nature of the networks firms utilize to access knowledge and facilitate innovation. The paper draws on the notion of network resources, distinguishing two types: social capital – consisting of the social relations and networks held by individuals; and network capital – consisting of the strategic and calculative relations and networks held by firms. The methodological approach consists of a quantitative analysis of data from a survey of firms operating in knowledge-intensive sectors of activity. The key findings include: social capital investment is more prevalent among firms frequently interacting with actors from within their own region; social capital investment is related to the size of firms; firm size plays a role in knowledge network patterns; and network dynamism is an important source of innovation. Overall, firms investing more in the development of their inter-firm and other external knowledge networks enjoy higher levels of innovation. It is suggested that an over-reliance on social capital forms of network resource investment may hinder the capability of firms to manage their knowledge networks. It is concluded that the link between a dynamic inter-firm network environment and innovation provides an alternative thesis to that advocating the advantage of network stability

University Patenting: Estimating the Diminishing Breadth of Knowledge Diffusion and Consumption

The rate of university patenting increased dramatically during the 1980s. To what extent did the knowledge flow patterns associated with public sector inventions change as university administrators and faculty seemingly became more commercially oriented? Using a Herfindahl-type measure of patent assignee concentration and employing a difference-in-differences estimation to compare university to firm patents across two time periods, we find that the university diffusion premium (the degree to which knowledge flows from patented university inventions are more widely distributed across assignees than those of firms) declined by over half during the 1980s. In addition, we find that the university diversity premium (the degree to which knowledge inflows used to develop patented university inventions are drawn from a less concentrated set of prior art holders than those used by firms) also declined by over half. Moreover, in both cases the estimated increase in knowledge flow concentration is largely driven by universities experienced in patenting, suggesting these phenomena are not likely to dissipate with experience.