Integrating IT-Enabled Social Networks with Transaction Cost Economics and the Resource Based View of the Firm

Prior research has mostly focused on transaction cost economics (TCE) to interpret the effect of information systems (IS) on organizational governance structures. A TCE based approach predicts that information technology (IT) will lead to increased use of electronic markets to coordinate economic transactions from electronic hierarchies. However, there is contradictory evidence in the literature regarding the rise and importance of cooperative relationships, joint ventures, and value-added partnerships integrated through information systems. To reconcile these contradictions, this paper analyzes the effect of IT on governance structures based on the TCE, social network theory, and the resource based view (RBV) of the firm. The most important aspect of this paper is that instead of overemphasizing the economic perspective, as has been done in prior IS research, it pays equal attention to economic, social, and knowledge perspectives of the firm. By considering variables such as product demand uncertainty, human specificity, task complexity, and frequency of interaction, the effect of IT on governance structure has been analyzed. In this paper, we suggest that, in knowledge intensive companies, a greater degree of outsourcing will take place, not through markets as hypothesized by earlier researchers, but through an increasing number of social networks. This differentiation can not be understood in simple economic terms because social networks are not based on contracts. Therefore, we suggest that the integration of IT-enabled social networks with the TCE and RBV of the firm leads to a better understanding and improvement of decision-making and corporate governance structures in knowledge intensive firms

Clinical significance of Phosphatidyl Inositol Synthase overexpression in oral cancer

<p>Abstract</p> <p>Background</p> <p>We reported increased levels of Phosphatidyl Inositol synthase (PI synthase), (enzyme that catalyses phosphatidyl inositol (PI) synthesis-implicated in intracellular signaling and regulation of cell growth) in smokeless tobacco (ST) exposed oral cell cultures by differential display. This study determined the clinical significance of PI synthase overexpression in oral squamous cell carcinoma (OSCC) and premalignant lesions (leukoplakia), and identified the downstream signaling proteins in PI synthase pathway that are perturbed by smokeless tobacco (ST) exposure.</p> <p>Methods</p> <p>Tissue microarray (TMA) Immunohistochemistry, Western blotting, Confocal laser scan microscopy, RT-PCR were performed to define the expression of PI synthase in clinical samples and in oral cell culture systems.</p> <p>Results</p> <p>Significant increase in PI synthase immunoreactivity was observed in premalignant lesions and OSCCs as compared to oral normal tissues (p = 0.000). Further, PI synthase expression was significantly associated with de-differentiation of OSCCs, (p = 0.005) and tobacco consumption (p = 0.03, OR = 9.0). Exposure of oral cell systems to smokeless tobacco (ST) in vitro confirmed increase in PI synthase, Phosphatidylinositol 3-kinase (PI3K) and cyclin D1 levels.</p> <p>Conclusion</p> <p>Collectively, increased PI synthase expression was found to be an early event in oral cancer and a target for smokeless tobacco.</p

Contractor Incentives for Success in Implementing Performance-Based Logistics: A Progress Report

Symposium Presentation (for Acquisition Research Program)Symposium PresentationNaval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

Minimizing flowtime subject to optimal makespan on two identical parallel machines

We consider the problem of scheduling jobs on two parallel identical machines where an optimal schedule is defined as one that gives the smallest total flowtime (the sum of the completion time of all jobs) among the set of schedules with optimal makespan (the completion time of the latest job). Utilizing an existing optimization algorithm for the minimization of makespan, we propose an algorithm to determine optimal schedules for this problem. We empirically show that the proposed algorithm can quickly find optimal schedules for problems containing a large number of jobs

Comparing backpropagation with a genetic algorithm for neural network training

This article shows that the use of a genetic algorithm can provide better results for training a feedforward neural network than the traditional techniques of backpropagation. Using a chaotic time series as an illustration, we directly compare the genetic algorithm and backpropagation for effectiveness, ease-of-use, and efficiency for training neural networks.Neural networks Backpropagation Genetic algorithm Empirical results