Creating Theoretical Research Frameworks using Multiple Methods

Sergey Samoilenko is an associate professor and the Chair of the Department of Computer Science and Computer Information Systems at Averett University, in Danville, Virginia. Sergey’s current research interests include IT and productivity, data mining, and IS development. He holds his PhD and MS in information systems from Virginia Commonwealth University. He has published in the European Journal of Operational Research, Journal of Global Information Technology Management, International Journal of Production Economics, Expert Systems with Applications, and Information Systems Frontiers, among other journals, as well as in numerous conference proceedings. Kweku-Muata Osei-Bryson is professor of Information Systems at Virginia Commonwealth University. Previously he was professor of information systems and decision analysis in the School of Business at Howard University, Washington, DC, USA. He has also worked as an information systems practitioner in both industry and government. His research areas include: Data Mining, Decision Support Systems, Knowledge Management, IS Security, e-Commerce, IT for Development, Database Management, IS Outsourcing, Multi-Criteria Decision Making. He has published in various leading journals including: Decision Support Systems, Information Systems Journal, Expert Systems with Applications, European Journal of Information Systems, Information Systems Frontiers, Knowledge Management Research & Practice, Information Sciences, Information & Management, Journal of the Association for Information Systems, Journal of Information Technology for Development, Journal of Database Management, Computers & Operations Research, Journal of the Operational Research Society, & the European Journal of Operational Research.

Introduction. Overview on ICT4D Research. Overview on Neo-Classical Growth Accounting. Overview on Chaos & Complex Systems Theory. Product Life Cycle Theory. Overview on Decision Tree Induction. Overview on Cluster Analysis. Overview on Data Envelopment Analysis (DEA). Overview on Structural Equation Modeling (SEM). Overview of Neural Networks (NN). Inquiry into heterogeneity of the competitive environment (by using CA). Investigation of the sources of heterogeneity of the competitive environment (by using DT). Assessment of the relative efficiency of competitors in heterogeneous environment(by using DEA and DT). Finding sources of relative inefficiencies in heterogeneous environment (by using DEA with MI and DT). Study of the role of a human capital in growth in productivity (by using DEA with SEM). Formulation of investment strategies driven by relative efficiency and growth in productivity (by using DEA with MI). Allocation of investments to optimize economic performance of the product (by using DEA applied to Product Life Cycle theory). Assessing the role of resources vs. utilization of resources in efficient production of economic outputs (by using NN).