Journal of Global Management Studies
Volume 2, Number 2
Interactive Responsibility among Organizations and Environments. David A. Handcock and Morton Cotlar
A New Approach to Optimal Investment Portfolio Management. Galia N. Nedeltcheva and Kenneth M. Ragsdell –
Cultural Influences on the Decision Process for Acquiring Enterprise Software: A Comparison of Mexico and United States. Jacques Verville, Ramaraj Palanisamy and Christine Bernadas
Balanced Scorecard and Determining the Relation of Strategic Goals and Performance Measures: Evidence, Semnan Province Tax Organizations of Iran. Mehdi Zaribaf and Baran Samandi
Automated Metadata for Image Mining. Faleh Al-Shameri
Interactive Responsibility among Organizations and Environments
David A. Hancock, D.M.
Cambium Break Consulting
1009 Queens Pl., Spring Hill TN 37174
Morton Cotlar, PhD, P.E.
University of Hawaii
1039 Kaalula Pl., Honolulu HI 96825
This paper describes a new model that can clarify relationships between organizations and their environments. It explains how organizations interact with environments and identifies eight environmental segments. These segments of the entire environment interact with each other, aggravating complexity of the whole that organizations face. Cited is the process of how original authorization from society creates organizational responsibilities (with accountabilities) and how their fulfillment can lead to organizational success in its society. Finally, the paper shows how this complex process is not unlike that of other living systems existing in a society, promoting a new understanding of organizations. This model inevitably leads to deeper understanding of organizations than classical organization behavior has provided. Societies may regard their organizations as susceptible to controls from some environmental segments, but often fail to recognize, in turn, the organizations’ responsibility to the complex environment of the society. People in such societies should understand the intricacy of interactions between organizations and their environments, particularly across today’s global milieu. Decision-makers in organizations need deep understanding of why their personal career success depends substantially on adequate fulfillment of their
A conclusion implies substantial improvement in organizational operations is possible, if decision makers gain thorough understanding of environmental complexity. Organizational productivity can improve from recognizing that organizations can be regarded as a field of living systems theory; this and attitudinal changes from training offers research opportunities to assess benefits from proposed mind-set changes. A basis for acknowledging greater
responsibility of organizations to their environments is critically needed globally.
Key Words: organizations, environments, behavior, living systems, responsibility, accountability, interactions
A New Approach to Optimal Investment Portfolio Management
Galia N. Nedeltcheva, Ph .D.
Postdoctoral Fellow, Design Engineering Center
Kenneth M. Ragsdell, Ph. D.
Professor, Design Engineering Center Director
Engineering Management and Systems Engineering
Missouri University of Science and Technology
Rolla, MO – USA
In this paper the authors show that historical data can be used to estimate three crucial parameters of the allocation model, i.e. not only maximizing expected return or minimizing expected risk, and maximizing the difference of expected return and expected risk, but also maximizing the portfolio stability. Stable portfolios consistently earn desired return on investment and appreciate in value irrespective of external economic environment, market
conditions and investor sentiments.
The present work discussed the application of the Taguchi System of Quality Engineering in order to show how portfolio stability can be measured by Signal-to-Noise ratio of the portfolio value. A stable portfolio exhibits consistent gain in the S/N ratio. The S/N ratio can be used instead of expected portfolio return as an objective optimization function as presented as shown in an example. Further, it is presented a Quality Engineering (QE) optimization portfolio formulation and the results from the portfolio management methodology that combines the principles of QE, Value Investing and forecasting show that it could beat the average market return with a huge margin.
Keywords: Optimal Portfolio Management, Taguchi System of Quality Engineering (TSQE) Portfolio Stability, Signal-to-Noise (S/N) ratio
Cultural Influences on the Decision Process for Acquiring Enterprise
Software: A Comparison of Mexico and United States
Faculty of Management, University of British Columbia – Okanagan,
Gerald Schwartz School of Business & Information Systems,
St. Francis Xavier University, Antogonish, Canada.
College of Education & Professional Studies, Central Washington University,
Ellensburg, Washington, DC, USA.
The acquisition of Enterprise Software (ES) is a high expenditure activity that is fraught with a high level of risk. Can we safely assume that the acquisition of ES is similar for all countries? A simple answer is that it is probably not due to fact that human beings are involved in the decision making process of acquiring ES, individuals from different cultural backgrounds may introduce their own cultural bias. The objective of this study is to answer the following question: in ES acquisition, are Mexican and US organizations influenced by the same factors? To answer the question a hybrid Structured Equation Modeling (SEM) study has been realized and confirmed by an ANOVA analysis. The results show that Mexican and U.S. firms are not influenced the same way or by the same influencing factors. “System”, “Integration” and “Team” factors influence Mexican organizations more than US organizations and “Users” factor influences US organizations more than Mexican organizations.
Keywords: Enterprise software, United States, Mexico, ERP acquisition, Influences, factors and culture.
Balanced Scorecard and Determining the Relation of Strategic Goals and
Performance Measures: Evidence, Semnan Province Tax Organizations of Iran
Mehdi Zaribaf, Ph.D.
Islamic Azad University
Islamic Azad University
Nowadays, organizations have been affected by competition and rapidly growth than other times, so they have realized the role of strategic management and the need for successful implementing and measuring of strategies. Supplying a system, that not only could measure their performances, but also control and implement strategies, is in fact considered as a blooming period in developing strategic management knowledge, and was highly embraced
by managers. Balanced scorecards have provided this by using non-financial performance measures in customer, internal process, and learning and growth perspectives together in balance with financial measures, and establishing cause and effect relationships, concerning organization's strategic objectives.
The present research aims to provide a BSC model in which all key performance activities, strategic objectives and evaluating measures of Semnan Tax Organizations defined in the framework of four perspectives of BSC model based on major strategies of Iran Tax Organization. Archival and field study tools have been used in this research. For identifying measures, tax experts and chief executive's viewpoints have been gathered, and for collecting
data, documents and records of Semnan Tax Offices and statistics available in Semnan Province, have been used at a period of 5 years (2004-2008). Through applying analysis of correlation, we have identified the relationships between variables (measures) and drew first strategy map. Then, for finding any other probable relationships not shown in previous stage, we used regression analysis method, which has led to draw the final strategy map.
Keywords: Balanced Scorecard, performance measurement, strategic management, strategy map, and strategy focused organization.
Automated Metadata For Image Mining
Faleh Alshameri, Ph. D.
University of Mary Washington
Data mining associated with massive datasets presents a major problem to the serious data miner. Datasets containing terabytes or more of data preclude any possibility of a human actually looking at the image database and manually categorizing the images. I propose an automated system for automatically scanning the database for certain statistically appropriate feature vectors, recording them as digital objects, and subsequently augmenting the metadata with the appropriate digital objects. The result is that the data miner can do a Boolean search on the augmented metadata and quickly reduce the number of objects to be scanned to a much smaller set of images. The MISR instrument of NASA JPL's satellite TERRA is an excellent prototype database for demonstrating feasibility. The instrument captures radiance measurements which can be converted to georectified images.
Keywords: GLCM, NDVI, AVI, entropy, energy, homogeneity, contrast