Measuring information security breach impact and uncertainties under various information sharing scenarios

This study draws on information theory and aims to provide simulated evidence using real historical and statistical data to demonstrate how various levels of integration moderate the impact and uncertainties of information security breach on supply chain performance. We find that the supply chain behaves differently under various levels of integration when a security breach occurs. The entropy analysis revealed that the wholesaler experience the most uncertainty under system failure and data corruption. This sort of impact-uncertainty information will aid in designing and managing a resilient supply chain poised for minimal breach impact

Organizational knowledge creation

The purpose of this paper is to present an overview of the state-ofthe- art in organizational knowledge creation, a field of research that is expanding almost exponentially. Knowledge creation is a dynamic capability that enables firms to achieve a sustainable competitive advantage on the market. Our purpose is to critically analyze the most significant ideas published in this field, and especially to present the most important models elaborated for organizational knowledge creation: Nonaka’s model, Nissen’s model, Boisot’s model, and the EO_SECI model. Also, we would like to identify the main determinants of the knowledge creation process.Ba, competitive advantage, knowledge, knowledge creation, SECI.

Development of an Approach for Analyzing Supply Chain Complexity

Supply chains are faced with a rising complexity of products, structures, and processes. Because of the strong link between a supply chain’s complexity and its efficiency the supply chain complexity management becomes a major challenge of today’s business management. A two dimensional driver concept is introduced and explained to comprehend the major causes of a supply chains’ complexity. To map the effects of the drivers and to understand the different dimensions of complexity, a general complexity model is introduced. A supply chain complexity analysis approach is presented, to evaluate the initial situation and to provide the necessary information for deriving the right actions and strategies for the management of complexity within a supply chain.complexity; supply chain; variety; model

Configurational Information as Potentially Negative Entropy: The Triple Helix Model

Configurational information is generated when three or more sources of variance interact. The variations not only disturb each other relationally, but by selecting upon each other, they are also positioned in a configuration. A configuration can be stabilized and/or globalized. Different stabilizations can be considered as second-order variation, and globalization as a second-order selection. The positive manifestations and the negative selections operate upon one another by adding and reducing uncertainty, respectively. Reduction of uncertainty in a configuration can be measured in bits of information. The variables can also be considered as dimensions of the probabilistic entropy in the system(s) under study. The configurational information then provides us with a measure of synergy within a complex system. For example, the knowledge base of an economy can be considered as such a synergy in the otherwise virtual (that is, fourth) dimension of a regime

Assessing the spatial distribution of crop production using a generalized cross-entropy approach:

While agricultural production statistics are reported on a geopolitical – often national - basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agro-ecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels' – typically 25 to 100 square kilometers in size. The information utilized includes crop production statistics, farming system characteristics, satellite-derived land cover data, biophysical crop suitability assessments, and population density. An application is presented in which Brazilian state level production statistics are used to generate pixel level crop production data for eight crops. To validate the spatial allocation we aggregated the pixel estimates to obtain synthetic estimates of municipio level production in Brazil, and compared those estimates with actual municipio statistics. The approach produced extremely promising results. We then examined the robustness of these results compared to short-cut approaches to spatializing crop production statistics and showed that, while computationally intensive, the cross-entropy method does provide more reliable estimates of crop production patterns.Entropy, Cross entropy, Remote sensing, Spatial allocation, Crop distribution,

Status report: Data management program algorithm evaluation activity at Marshall Space Flight Center

An algorithm evaluation activity was initiated to study the problems associated with image processing by assessing the independent and interdependent effects of registration, compression, and classification techniques on LANDSAT data for several discipline applications. The objective of the activity was to make recommendations on selected applicable image processing algorithms in terms of accuracy, cost, and timeliness or to propose alternative ways of processing the data. As a means of accomplishing this objective, an Image Coding Panel was established. The conduct of the algorithm evaluation is described