Information Systems in Management Science—Teaching the Foundations for the Economic Analysis and Evaluation of Information Systems

Changing the qualification structure of contractors for the subsystem (function) of analytical processing of technical and economic information data (systematic economic analysis, evaluation) at industrial enterprises and scientific and industrial associations, should also strive to ensure that the economic efficiency of economic and analytical work in the sense of its scientific level, results achieved, reliability and timing was highest, and the use of potential staff capabilities was greatest. It is about optimizing the activity of subsystem staff. In this regard, one of the thematic issues of organizational support for the subsystem (function) of analytical processing of technical and economic information data (systematic economic analysis and evaluation) is the development of a system of measures that ensure the subordination of activities of personnel to the goals set both before the subsystem and before the system. Management of an industrial enterprise and a scientific-industrial association as a whole, and of those that certainly contribute to the most cost-effective implementation of this economic activity in set direction of development. The whole range of problems of comprehensive provision in functionally developed systems of strategic management of special purpose scientific and industrial associations and enterprises of the industry cost-effective activities of personnel of the subsystem (function) of analytical processing of technical and economic information data (systematic economic analysis and evaluation) should be solved on the basis of system approach. The shift in the process of designing the center of gravity of research towards the utilization of the capabilities of the human component of the subsystem (function) is one of the most important and indispensable conditions for the effectiveness of its organizational support, and accordingly, to obtain a given economic (economic) effect from the functional development of the subsystem (function) of analytical processing-economic information empiric (data) (systematic economic analysis and evaluation).

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Adaptive Information Systems and Modelling in Economics and Management Science

10.1007/3-211-29901-7 ◽

2005 ◽

Cited By ~ 1

Keyword(s):

Information Systems ◽

Management Science

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Book Reviews

INFORMS Journal on Applied Analytics ◽

10.1287/inte.2021.1071 ◽

2021 ◽

Vol 51 (3) ◽

pp. 242-244

Author(s):

Wenjing Shen

Keyword(s):

Big Data ◽

Information Systems ◽

Operations Research ◽

Management Science ◽

Diverse Range ◽

Optimization And Control ◽

Areas Of Interest ◽

And Control ◽

To Receive

In Book Reviews, we review an extensive and diverse range of books. They cover theory and applications in operations research, statistics, management science, econometrics, mathematics, computers, and information systems. In addition, we include books in other fields that emphasize technical applications. The editor will be pleased to receive an email from those willing to review a book, with an indication of specific areas of interest. If you are aware of a specific book that you would like to review, or that you think should be reviewed, please contact the editor. The following books are reviewed in this issue of INFORMS Journal on Applied Analytics, 51(3), May–June: Optimization and Control for Systems in the Big-Data Era: Theory and Applications, Tsan-Ming Choi, Jianjun Gao, James H. Lambert, Chi-Kong Ng, Jun Wang; Pricing Lives: Guideposts for a Safer Society, W. Kip Viscusi.

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Ontological Analysis of Reference Models

Business Systems Analysis with Ontologies ◽

10.4018/978-1-59140-339-5.ch003 ◽

2011 ◽

pp. 56-81 ◽

Cited By ~ 8

Author(s):

Peter Fettke ◽

Peter Loos

Keyword(s):

Information Systems ◽

Reference Model ◽

Point Of View ◽

Model Quality ◽

Analysis And Evaluation ◽

Reference Models ◽

Planning And Control ◽

Sound Theory ◽

Ontological Analysis ◽

And Control

Within the information systems field, reference models have been known for many years. A reference model is a conceptual framework and may be used as a blueprint for information systems development. Despite the relevance of reference model quality, little research has been undertaken on their systematical analysis and evaluation. In this chapter, we describe how reference models can be analyzed from an ontological point of view. Such an analysis consists of four steps: 1) developing a transformation mapping, 2) identifying ontological modeling deficiencies, 3) transforming the reference model, and 4) assessing the results. The usefulness of our method will be demonstrated by analyzing Scheer’s reference model for production planning and control. Although our approach is based on sound theory, we argue that this approach is not inherently superior to other approaches of reference model analysis and evaluation.

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Development and Design Methodologies in DWM

Enterprise Information Systems ◽

10.4018/978-1-61692-852-0.ch213 ◽

2011 ◽

pp. 533-543

Author(s):

James Yao ◽

John Wang ◽

Qiyang Chen ◽

June Lu

Keyword(s):

Decision Making ◽

Information Systems ◽

Management Information Systems ◽

Systems Design ◽

Management Science ◽

Science Journal ◽

Management Information ◽

Research Papers ◽

Systems Research ◽

Information Systems Research

Information systems were developed in early 1960s to process orders, billings, inventory controls, payrolls, and accounts payables. Soon information systems research began. Harry Stern started the “Information Systems in Management Science” column in Management Science journal to provide a forum for discussion beyond just research papers (Banker & Kauffman, 2004). Ackoff (1967) led the earliest research on management information systems for decision-making purposes and published it in Management Science. Gorry and Scott Morton (1971) first used the term decision support systems (DSS) in a paper and constructed a framework for improving management information systems. The topics on information systems and DSS research diversifies. One of the major topics has been on how to get systems design right.

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