Conceptual Design of a Method to Support IS Security Investment Decisions within the Context of Critical Business Processes

The author of this chapter worked for 42 years in the construction industry. Employed by a company with great leadership, vision and values. The author was able to evolve from the pencil and paper applications to the latest in data acquisition, analysis and modeling. Simulation modeling and business science were successfully applied to many business functions with significant results in predicting risk and uncertainty ranges before bids, projects and investment decisions were complete. Included in this chapter are samples of Strategic Bidding, Cost (Range) Estimating, Scheduling, Project Management/Control, and Corporate Resource Management. Business processes can be measured for Stability, Capability and Predictability. Consistently balancing decisions within the upper and lower control limits, using valid reasoning for taking advantage of risk or opportunity will usually guarantee long term success. Reality can be a friend if it is measured and applied with the right expectations. Modeling creates the environment for tapping into substance and understanding.

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Stock Fundamentals Model Based on Genetic Algorithm-Rough Set

Journal of Management and Sustainability ◽

10.5539/jms.v6n1p206 ◽

2016 ◽

Vol 6 (1) ◽

pp. 206

Author(s):

Weizhong Jiang ◽

Xi Xie

Keyword(s):

Genetic Algorithm ◽

Rough Set ◽

Investment Decisions ◽

Index Selection ◽

Security Investment ◽

Technical Indicators ◽

Highly Nonlinear ◽

Improved Model ◽

Lower Uncertainty ◽

Prediction Evaluation

<p>Security investment problems are mostly highly-nonlinear and have huge operations, hence quantitative investment is applied to make decisions frequently. Considering the example of Medicine plate in Chinese stocks, fundamental indicators and technical indicators are combined, and then investment decisions are made and optimized stepwise based on rough set model, where generical gorithm is applied to solve the model, aiming at searching for a portfolio with high value and growth inside the whole medicine plate. In addition, such strategy elements as trend and goodness are considered in the prediction, evaluation and correction of the model, resulting in lower uncertainty of index selection. In the empirical example, with the use of the improved model, stock rankings inside the plate achieve an accuracy of 60.7%, which proves the model makes sense to some extent in the security investment.</p>

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Relational Service Quality Modeling

Non-Functional Properties in Service Oriented Architecture ◽

10.4018/978-1-60566-794-2.ch008 ◽

2011 ◽

pp. 172-193

Author(s):

Vladimir A. Shekhovtsov ◽

Roland Kaschek ◽

Christian Kop ◽

Heinrich C. Mayr

Keyword(s):

Normal Form ◽

Service Quality ◽

Conceptual Design ◽

Business Processes ◽

Requirements Elicitation ◽

Application System ◽

Service Orchestration ◽

Quality Requirements ◽

Requirements Modeling ◽

Quality Modeling

The paper argues that using non-first-normal-form (NF2) tables for requirements modeling is a suitable approach for communicating application system issues to stakeholders who have a business background. In particular, such tables are used in an intermediate predesign step residing between requirements elicitation and conceptual design for modeling functional and quality requirements of services and business processes. This approach extends to quality requirements of business processes used for service orchestration.

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Capacity Management Business Processes

Business Processes ◽

10.4018/978-1-59140-979-3.ch009 ◽

2011 ◽

pp. 194-219

Author(s):

Victor Portougal

Keyword(s):

Long Range ◽

Business Processes ◽

Investment Decisions ◽

Capacity Management ◽

Senior Management ◽

The Other ◽

Trade Off ◽

Additional Capacity ◽

Market Pressures ◽

A Company

The company is always aware of what it wants to produce because it is definedby the market pressures or by demand. However, what the company wants tomake must be rationalised against what it can make. The issue of balancebetween requirements and capacity relates to a type of trade off. On one hand,the company wants to satisfy demand, but on the other hand, it may not havethe capital resources to do so. At the senior management strategic planninglevel, long-range investment decisions are made that can increase the company’scapacity resources. Commonly however, the additional capacity lags behindthe pressure to produce more product more quickly. In these cases, manage-ment must make choices. A company must select carefully how to manage itslimited asset of resources to achieve the greatest benefit to the company.

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Corporate Information Security Investment Decisions

International Journal of Enterprise Information Systems ◽

10.4018/ijeis.2018040101 ◽

2018 ◽

Vol 14 (2) ◽

pp. 1-20 ◽

Cited By ~ 3

Author(s):

Daniel Schatz ◽

Rabih Bashroush

Keyword(s):

Information Security ◽

Investment Decisions ◽

Business Leaders ◽

Theory Approach ◽

Executive Directors ◽

Key Factors ◽

Security Investment ◽

Grounded Theory Approach ◽

Information Security Investment ◽

Corporate Information

This article describes how with information security steadily moving up on board room agendas, security programs are found to be under increasing scrutiny by practitioners. This level of attention by senior business leaders is new to many security professionals as their field has been of limited interest to non-executive directors so far. Currently, they have to regularly report on efficiency and value of their security capabilities whilst being measured against business priorities. Based on the Grounded Theory approach, the authors analysed the data gathered in a series of interviews with senior professionals in order to identify key factors in the context of information security investment decisions. The authors present detailed findings in context of a simplified framework that security practitioners can utilise for critical review or improvements of investment decisions in their own environments. Extensive details for each category as extracted through a qualitative data analysis are provided along with a category network analysis that highlights strong relationships within the framework.

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