Kristin Kennedy, Sam Mirmirani and Rick Spivack
One aspect of the Clinton Healthcare Reform programme is to assist health maintenance organizations (HMOs) in collecting and analysing data for the purpose of continuous quality…
Abstract
One aspect of the Clinton Healthcare Reform programme is to assist health maintenance organizations (HMOs) in collecting and analysing data for the purpose of continuous quality improvement. The HEDIS 2.0 quality performance measurement model is currently in use and endorsed by the National Committee for Quality Assurance (NCQA). Outlines a process using HEDIS 2.0 by which an HMO can identify crucial problem areas and track the success of the solution process. Discusses the use of other relevant statistical tools.
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Sam Mirmirani and Hsi Cheng Li
This study applies VAR and ANN techniques to make ex-post forecast of U.S. oil price movements. The VAR-based forecast uses three endogenous variables: lagged oil price, lagged…
Abstract
This study applies VAR and ANN techniques to make ex-post forecast of U.S. oil price movements. The VAR-based forecast uses three endogenous variables: lagged oil price, lagged oil supply and lagged energy consumption. However, the VAR model suggests that the impacts of oil supply and energy consumption has limited impacts on oil price movement. The forecast of the genetic algorithm-based ANN model is made by using oil supply, energy consumption, and money supply (M1). Root mean squared error and mean absolute error have been used as the evaluation criteria. Our analysis suggests that the BPN-GA model noticeably outperforms the VAR model.
Hsi Chang Li, Sam Mirmirani and Joseph A. Ilacqua
The purpose of this paper is to focus on Confucius Institutes and assess the applicability of theories of leadership and knowledge sharing to multinational organizations and…
Abstract
Purpose
The purpose of this paper is to focus on Confucius Institutes and assess the applicability of theories of leadership and knowledge sharing to multinational organizations and worldwide networks. Growth of multinational trade and decrease in international tension have facilitated the globalization of both profit‐seeking and non‐profit organizations. Changes in economic and political environment have also blurred the divide in management practices between these organizations.
Design/methodology/approach
The research applies recent theoretical developments to analyze leadership and knowledge sharing of the highly successful Confucius Institutes. Operational similarities and differences between this global learning organization and multinational businesses are evaluated.
Findings
Many similarities exist between the operations of the Confucius Institutes and multinational businesses. For both, strategic goals are achieved through the promotion of global expansion and the management practices of distributed leadership and knowledge sharing. The study makes clear the successful application of distributed leadership to a worldwide network. The Confucius Institutes reflect the cultural and social changes in China, combined with influences of global cultures. Findings suggest that distributed leadership is a suitable management style for coping with variant cultural and socio‐political conditions globally. This leadership style, combined with a knowledge‐sharing network, is also suitable for the situational variables encountered in making thousands of decisions across hundreds of global locations by both learning institutions and business organizations.
Originality/value
The paper explores a relatively new area of the similarities and differences between global non‐profit and business networks as learning organizations. The study is of value to both those managing and those studying such organizations.
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Artificial intelligence is a consortium of data-driven methodologies which includes artificial neural networks, genetic algorithms, fuzzy logic, probabilistic belief networks and…
Abstract
Artificial intelligence is a consortium of data-driven methodologies which includes artificial neural networks, genetic algorithms, fuzzy logic, probabilistic belief networks and machine learning as its components. We have witnessed a phenomenal impact of this data-driven consortium of methodologies in many areas of studies, the economic and financial fields being of no exception. In particular, this volume of collected works will give examples of its impact on the field of economics and finance. This volume is the result of the selection of high-quality papers presented at a special session entitled “Applications of Artificial Intelligence in Economics and Finance” at the “2003 International Conference on Artificial Intelligence” (IC-AI ’03) held at the Monte Carlo Resort, Las Vegas, NV, USA, June 23–26 2003. The special session, organised by Jane Binner, Graham Kendall and Shu-Heng Chen, was presented in order to draw attention to the tremendous diversity and richness of the applications of artificial intelligence to problems in Economics and Finance. This volume should appeal to economists interested in adopting an interdisciplinary approach to the study of economic problems, computer scientists who are looking for potential applications of artificial intelligence and practitioners who are looking for new perspectives on how to build models for everyday operations.
Massimiliano Matteo Pellegrini, Francesco Ciampi, Giacomo Marzi and Beatrice Orlando
Effectively handling knowledge is crucial for any organization to survive and prosper in the turbulent environments of the modern era. Leadership is a central element for…
Abstract
Purpose
Effectively handling knowledge is crucial for any organization to survive and prosper in the turbulent environments of the modern era. Leadership is a central element for knowledge creation, acquisition, utilization and integration processes. Based on these considerations, this study aims to offer an overview of the evolution of the literature regarding the knowledge management-leadership relationship published over the past 20 years.
Design/methodology/approach
A bibliometric analysis coupled with a systematic literature review were performed over a data set of 488 peer-reviewed articles published from 1990 to 2018.
Findings
The authors discovered the existence of four well-polarized clusters with the following thematic focusses: human and relational aspects, systematic and performance aspects, contextual and contingent aspects and cultural and learning aspects. The authors then investigated each thematic cluster by reviewing the most relevant contributions within them.
Research limitations/implications
Based on the bibliometric analysis and the systematic literature review, the authors developed an interpretative framework aimed at uncovering several promising and little explored research areas, thus suggesting an agenda for future knowledge management-leadership research. Some steps of the paper selection process may have been biased by the interpretation of the researcher. The authors addressed this concern by performing a multiple human subject reading process whose reliability was confirmed by a Krippendorf’s alpha coefficient value >0.80.
Originality/value
To the best knowledge, this is the first study to map, systematize and discuss the literature concerned to the topic of the knowledge management-leadership relationship.