Goal-oriented design of value and process models from patterns

This thesis defines a design framework and a method for modelling networked businesses. The intended application domain is electronic businesses that extensively use information and communication technology to coordinate work. The key property of the proposed approach is the reuse of design knowledge in the form of design patterns. Design patterns are extracted from models of existing electronic intermediaries considered successful. These businesses have been reverse-engineered to two types of models: economic value exchange models and business process models. The identified patterns comprise two libraries of value exchange and business process patterns, respectively. Patterns are catalogued with, among others, their context, solved problem, and proposed solution. Most importantly, they are annotated with a machine-readable\ud capability model used as a search key in the library. Capability models are part of the goal-modelling technique for business requirements proposed here. Our goal-modelling technique operationalizes each business goal with a variable and an evaluation function: the evaluation function determines when a measured variable value satisfies the goal. A goal model represents requirements if goals are assigned evaluation functions but the variable values are unknown. In such a case, the goal model specifies what is desired to happen. If, on the other hand, variable values are known, the goal model documents the capabilities of a pattern. The proposed design framework structures the development process into: (1) available design knowledge in libraries of value and process patterns, (2) business requirements captured in a goal model, and (3) economic value and business process perspectives to look at a business system. The design method prescribes steps to transform patterns and requirements into a system specification. These include: (i) identification of relevant pattern based on matching capability and requirements goal models; (ii) synthesis of value and process patterns into value and process models, respectively; and (iii) consistency check procedure for value and process model.\ud The usefulness of the approach is demonstrated in a real-life example, which shows that the framework and method exhibit a predefined set of desired properties

Welfare gains from the adoption of proportional taxation in a general-equilibrium model with a grey economy: the case of Bulgaria's 2008 at tax reform. Technical Appendix

This is the Technical appendix to the article published in Economic Change and Restructuring 48(2), 2015

The welfare effect of at income tax reform: the case of Bulgaria. Technical Appendix

This is the detailed technical appendix for the model described in "The welfare effect of at income tax reform: the case of Bulgaria," published in Vol. 53(3), June 2015 by the Eastern European Economics

The Role of DBMS in Analytical Processes of the Logistic of Stock Reserves

One of main problems of corporate information systems is the precise evaluation of speed of transactions and the speed of making reports. The core of the problem is based on the DBMS that is used. Most DBMS which are oriented for high performance and reliability of transactions do not give fast access to analytical and summarized data and vice versa. It is quite difficult to estimate which class of database to use. The author of the article gives a concise observation of the problem and a possible way to be solved

The minimal conformal O(N) vector sigma model at d=3

For the minimal O(N) sigma model, which is defined to be generated by the O(N) scalar auxiliary field alone, all n-point functions, till order 1/N included, can be expressed by elementary functions without logarithms. Consequently, the conformal composite fields of m auxiliary fields possess at the same order such dimensions, which are m times the dimension of the auxiliary field plus the order of differentiation.Comment: 15 page

Coping With Antiglobalization: A Critique

Coping With Antiglobalization: A Critique

Application of Monte Carlo Methods: Computing Heterogeneous Agent Models Without Aggregate Uncertainty

In this paper we solve the benchmark heterogeneous agents model by Aiyagari (1994) using Monte Carlo methods. In addition, the idiosyncratic shocks process is approximated using Tauchen's (1986) method. This we go beyond the 2 by 2 Markov matrix approximation of the AR(1) stochastic process. The code is written in MATLAB. The computation time is much faster than the one written by Heer and Maussner (2008) in FORTRAN. This model also solves Mehra-Prescott's puzzle and generates a risk-free interest rate that is much closer to the one we observe in data