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Related Concept Videos

Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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Decision Making: Traditional Method01:14

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Mechanistic Models: Overview of Compartment Models01:21

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Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
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Econometric Views (EViews)01:29

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Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Related Experiment Video

Updated: May 16, 2025

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
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Enterprise modelling for decision-making in the software ecosystem.

Anshul Rani1, Deepti Mishra2, Aida Omerovic3

  • 1Department of Computer Science (IDI), Norwegian University of Science and Technology, Gjøvik, Norway. anshul.rani@ntnu.no.

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Summary

This study compares 4EM and ArchiMate for software outsourcing process modeling, finding ArchiMate more suitable. Models were validated, suggesting areas for digital innovation and further expert review.

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Area of Science:

  • Enterprise Systems Engineering
  • Software Process Modeling

Background:

  • Professionals face uncertainty in efficient process model development within the software ecosystem.
  • Existing enterprise modeling frameworks offer abstract guidance, limiting direct real-world application.

Purpose of the Study:

  • To compare 4EM and ArchiMate for software outsourcing process modeling.
  • To demonstrate appropriate views for modeling software vendor selection decision-making.
  • To assess the suitability of 4EM and ArchiMate in the software ecosystem context.

Main Methods:

  • Comparative analysis of 4EM and ArchiMate features for software outsourcing.
  • Modeling a software vendor selection decision-making scenario.
  • Validation of developed models using the SEQUAL framework.

Main Results:

  • ArchiMate demonstrated better suitability for the specific software outsourcing decision-making context.
  • Model validation led to the identification of a new process activity and potential for digital innovation.
  • The SEQUAL framework was used for validation, identifying areas for improvement.

Conclusions:

  • ArchiMate is recommended over 4EM for modeling software outsourcing decision-making processes.
  • Further validation with industry experts in real-world settings is necessary to refine the models.
  • The study provides a foundation for enhancing enterprise business process modeling in software outsourcing.