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It is demonstrated that entropy is a useful measure for examining
industrial diversity either among regions or for a particular region
over time. Using the entropy method, employment diversity indices are
computed for the 50 states and the district of Columbia for the ten‐year
period from 1972 to 1981. Of the 51 study areas, roughly half show high
to moderate diversification, and none are distinguished as either highly
diversified or highly specialised. Furthermore, the entropy measure is
disaggregated into its between‐set and within‐set elements to express
the extent and pattern of dispersal between and within different groups
and subsets of industries in the United States for the 28‐year period
from 1960 to 1987. The US economy is found to be relatively diversified
in terms of employment over the period of study. However, there is a
decreasing contribution of manufacturing and an increasing contribution
of non‐manufacturing to the degree of economic diversification within
the total economy.

Brain networks are widely used models to understand the topology and organization of the brain. These networks can be represented by a graph, where nodes correspond to brain regions and edges to structural or functional connections. Several measures have been proposed to describe the topological features of these networks, but unfortunately, it is still unclear which measures give the best representation of the brain. In this paper, we propose a new set of measures based on information theory. Our approach interprets the brain network as a stochastic process where impulses are modeled as a random walk on the graph nodes. This new interpretation provides a solid theoretical framework from which several global and local measures are derived. Global measures provide quantitative values for the whole brain network characterization and include entropy, mutual information, and erasure mutual information. The latter is a new measure based on mutual information and erasure entropy. On the other hand, local measures are based on different decompositions of the global measures and provide different properties of the nodes. Local measures include entropic surprise, mutual surprise, mutual predictability, and erasure surprise. The proposed approach is evaluated using synthetic model networks and structural and functional human networks at different scales. Results demonstrate that the global measures can characterize new properties of the topology of a brain network and, in addition, for a given number of nodes, an optimal number of edges is found for small-world networks. Local measures show different properties of the nodes such as the uncertainty associated to the node, or the uniqueness of the path that the node belongs. Finally, the consistency of the results across healthy subjects demonstrates the robustness of the proposed measures ; This work was supported by the Spanish Government (Grant No. TIN2016-75866-C3-3-R ) and by the Catalan Government (Grant No. 2017-SGR-1101). Data were provided, in part, by the Human ...

"The importance of benchmarking in the service sector is well recognized as it helps in continuous improvement in products and work processes. Through benchmarking, companies have strived to implement best practices in order to remain competitive in the product- market in which they operate. However studies on benchmarking, particularly in the software development sector, have neglected using multiple variables and therefore have not been as comprehensive. Information Theory and Best Practices in the IT Industry fills this void by examining benchmarking in the business of software development and studying how it is affected by development process, application type, hardware platforms used, and many other variables. Information Theory and Best Practices in the IT Industry begins by examining practices of benchmarking productivity and critically appraises them. Next the book identifies different variables which affect productivity and variables that affect quality, developing useful equations that explaining their relationships. Finally these equations and findings are applied to case studies. Utilizing this book, practitioners can decide about what emphasis they should attach to different variables in their own companies, while seeking to optimize productivity and defect density."--Publisher's website

We argue that the burgeoning literature on policy transfer suffers from the lack of an analytical framework that would facilitate understanding &, thus, theory building. We suggest that policy transfer be conceptualized as occurring through a communications & information framework & that it focus on information networks that include producers, senders, & facilitators of information, as well as recipients. We apply this framework to an illustrative study of how British local authority officials involved in the area of urban regeneration policy learn from each other's experience. Utilizing this approach, the results of our case study yield several testable hypotheses for future study. In particular, they direct us toward the importance of informal networks in the policy-transfer process; toward an examination of the motivations of producers, senders, & disseminators of information; & toward the difficulty all participants in the network have in assessing the quality & validity of the information they receive. 4 Tables, 31 References. Adapted from the source document.