A Cross-National Comparison E-government Success Measures: A Theory-Based Empirical Research

The continuing rapid convergence of government and e-technologies presents new opportunities for research to investigate the ways citizens interact with e-government. The literature in the area is, however, still in its infancy with little or no theoretically grounded empirical research conducted in the area. The present research investigates citizen experience with e-government in the United States and Spain by utilizing difference tests. Results of the difference tests show that the Spanish e-government citizens put more emphasis on information quality in terms of relevance, reliability, timeliness, clarity, conciseness, and currency. Results of the difference tests also show that for the system usage construct, e-government citizens on both side of the Atlantic agree that their e-government should provide superior user training, facilitate use of extranets to communicate with governmental agencies, allow automated transmitting and processing of data, and allow real time monitoring of citizen request for information in an e-government integrated with governmental agencies environment

A smart grids knowledge transfer paradigm supported by experts' throughput modeling artificial intelligence algorithmic processes

This paper presents an artificial intelligence algorithmic knowledge transfer approach to the models that have been developed throughout the world for smart grid networks. Many nations are moving forward to implement smarter ways to generate, distribute and network energy, while others are expecting the leading countries to take the initiative and then follow suit. Therefore, we theoretically identify three dimensions of experts' competencies—perception, judgment, and decision choice supported by the Throughput Model algorithms for knowledge transfer. Integrating the Throughput Model algorithmic framework and Deming Cycle (i.e., plan, do, check, act), we propose that Information and Communication Technology (ICT) systems influence experts' decision making towards implementation of Smart Grids (SG). This model was backed up with the perspectives of 32 global experts as surveyed using Carnegie Mellon Maturity model questions and analyzed the results using PLS to validate the findings and compare them to our enhanced knowledge transfer developed from Deming's PDCA cycle. Our results suggest that these key algorithmic decision-making components are critical in explaining the successful application of planning, doing, checking/ acting, and planning of renewable energy technology as well as for a greener environment