Rajendra Kulkarni

Spatial Small Worlds: New Geographic Patterns for an Information Economy

Networks are structures that pervade many natural and manmade phenomena. Recent findings have characterized many networks as not random chaotic structures but as efficient complex formations. Current research has examined complex networks as largely a nonspatial phenomenon. Location, distance, and geography, though, are all vital aspects of a wide variety of networks. The authors examine the US portion of Internet infrastructure as a complex network and the role distance and geography play in its formation. From these findings implications are drawn on the economic, political, national security, and technological impacts of network formation and evolution in an information economy.

An Application of Complex Network Theory to German Commuting Patterns

Simulating the structure and evolution of complex networks is an area that has recently received considerable attention. Most of this research has grown out of the physical sciences, but there is growing interest in their application to the social sciences, especially regional science and transportation. This paper presents a network structure simulation experiment utilizing a gravity model to identify interactions embodied in socio-economic processes. In our empirical case, we consider home-to-work commuting patterns among 439 German labour market districts. Specifically, the paper examines first the connectivity distribution of the German commuting network. The paper next develops a spatial interaction model to estimate the structure and flows in the network concerned. The focus of this paper is to examine how well the spatial interaction model replicates the structure of the German commuting network as compared to complex network models. Finally, the structure of the physical German road network is compared to the spatial flows of commuters across it for a tentative supply-demand comparison.

ICT and Knowledge Challenges for Entrepreneurs in Regional Economic Development

This paper examines the knowledge needs of entrepreneurs in a regional context with particular emphasis on the information and communication technology (ICT) industry sector. The paper begins by clarifying and defining the basic concepts. This is followed by the introduction of the entrepreneurial fountain as a model of the entrepreneurial milieu and as a framework for examining factors that influence the expansion and contraction of knowledge and entrepreneurial activity. The role knowledge plays in entrepreneurial discovery and action is thus examined and the implications are examined. The paper ends with a set of conclusions and recommendations for future research.

Moving from Protection to Resiliency: A Path to Securing Critical Infrastructure

The events of 9/11 brought renewed focus to critical infrastructure, but the security of infrastructure has been and continues to be an issue outside the scope of any one event or country. Oil pipeline attacks in Iraq, massive blackouts in Italy, the United States, and Russia, submarine cable failures in the Atlantic, accidental and intentional failures of infrastructure are an increasing and complex problem. The issue of infrastructure security is a global problem both is applicability and connectivity. All nations are dependent on infrastructure and many of these infrastructures cross international borders and some span the globe. A problem facing all nations is that they have the responsibility for securing infrastructure but critical aspects are owned by the private sector. This though is only one of many problems facing infrastructure security: 1) infrastructures are interdependent on each others reliability 2) infrastructures are large, dynamically unsynchronized, and complex 3) sharing information about infrastructure vulnerabilities is severely hampered by fears of regulation and competition. Along with these direct obstacles there are larger economic forces that complicate the issue. The markets driving infrastructure are geared towards maximizing efficiency to increase profit and not maximizing protection, which can result in public vulnerabilities.

Spin glass and the interactions of congestion and emissions: An exploratory step

Traffic congestion formation on roadways s modeled by recognition of the centrality of dynamical systems and by using concepts from complexity theory as imbedded in the spin glass analogue. It also explores the concept of how an increase in air pollution caused by vehicle exhaust emission can be traced to traffic congestion, specifically to the acceleration/deceleration of vehicles on the road. Spin glass is first introduced and then by applying the 2-D x-y Ising model and defining a Hamiltonian for a system of vehicles on the road, derivations are made of the specific friction of congestion and the bulk modulus of congestion using the Gibbs-Boltzmann statistic. Similarly, using the interactions of vehicles with each other and the resulting accelerations and decelerations of vehicles as the basis for exhaust emissions, derivations are made of a specificity of exhaust emissions. These are analogs to the entropy models of thermodynamics. This series of derivations serves as an analytical model for detecting incidents of congestion and increase in air pollution due to exhaust emissions in transportation systems.

Revisiting Night Lights as Proxy for Economic Growth: A Multi-Year Light Based Growth Indicator (LBGI) for China, India and the U.S.

In this paper we explore how satellite images of global night lights from the years 2001 to 2007 can be used to estimate economic activity at the sub-regional level in the U.S., India and China. The night lights based estimates of economic activity are then spatially analyzed and compared with sub-regional economic indicators where available for selected years. For this purpose we have extended the standard bi-variate LISA (Local Indicators of Spatial Autocorrelation) to include bi-directional analysis. This bi-directional bi-variate analysis helps to identify those jurisdictions where night lights intensity can be used as a proxy for measuring sub-regional economic growth. We also briefly discuss two theoretical models that shed light on the geospatial patterns reflected by the night light data. The results are presented with a series of maps, charts and tables.

Towards Modeling of Communities of Practice (CoPs): A Hebbian Learning Approach to Organizational Learning

Abstract This article addresses the issue of group learning, which is an emerging philosophy in the field of organizational learning. Although not all groups learn, those that do and form spontaneously have been referred to as Communities of Practice (CoPs). These groups appear to be very important among professional and dynamically interactive organizations. Members of such groups come together mainly due to exposure to a set of shared problems, professional and/or social. These members interact directly and use each other as sounding boards for new ideas and help each other learn. Both the business and academic fields have come to recognize CoPs as one of the most important structures in learning institutions or organizations. Identification, cultivation and maintenance of such groups has become a key issue in the field of knowledge management. If CoPs are one of the mechanisms by which organizations learn then it would be useful to acquire greater insight into these groups. In this article, we propose an analytical model of CoPs based on the neural network concept of Hebbian learning. Computer simulations are used to test the analytical model.

Towards an Information Entropy Model of Job Approval Rating: The Clinton Presidency

Director, The Institute of Public Policy, University Professor/Eminent Scholar, Professor of DecisionSciences, Geography and Public Affairs, George Mason University, Fairfax, VA 22030, USA*Author to whom correspondence should be addressed.Received: 3 September 1999 / Accepted: 27 September 1999 / Published: 30 September 1999Abstract: This paper discusses an analytical approach to explaining a nearly constant highjob approval rating of president Clinton between January, 1998 and February, 1999. Despiteall the controversy and massive information exposure to mostly unflattering news about Mr.Clinton; the public, in nearly all major opinion polls expressed their wish that Mr. Clintonbe allowed to complete his second term in the office. The analytical approach is based onthe information entropy theory of Shannon. The model is tested using the data from thepolling archives of ABC/Washington Post. The results are confirmed by the Kendalls τstatistics.Keywords: Clinton Presidency, Presidents job approval rating, Public opinion polls,Information entropy, Relative entropy

Light based growth indicator (LBGI): exploratory analysis of developing a proxy for local economic growth based on night lights

In this paper we explore how satellite images of global night lights from year 1992 to 2003 can be used to estimate economic activity at the sub-regional level in the U.S. and China. The night lights based estimates of economic activity are then spatially analyzed and compared with sub-regional economic indicators where available for selected years. We also briefly discuss two theoretical models that shed light on the geospatial patterns reflected by the night light data. The results are presented with a series of maps, charts and tables

PLACING INNOVATION: AN APPROACH TO IDENTIFYING EMERGENT TECHNOLOGICAL ACTIVITY

Identifying the elements of physical and organizational infrastructure most important for technological innovation is challenging for at least two reasons: measuring technological innovation is difficult; and establishing causality is difficult. In this paper, we partially address these paired challenges by (1) describing a new approach for measuring innovation, and (2) employing that approach to compare established technology regions with emerging ones, and to describe how technologies migrate as they develop.