Nowadays enterprises are considering economics grow based on exportations. When we go into the study of migrant groups, experiences and cultural contexts established in deep-rooted ancestral customs that allow us to identify problems and opportunities in the context of supply and demand for products. Being this the precursor of market opportunities that are created in both the host countries and in emerging or developing countries. Companies in relevant markets are building international brands supporting these somewhat vulnerable populations to change their living conditions, in order to provide a vision of opportunity. Given this increasingly representative worldwide phenomenon, this paper aims to focus the ways in which some of the companies captivated by relevant markets are facing the challenges and taking advantage of the multiplier effect and expansion wave to give sustainability to their markets.
Fuzzy cognitive maps have received increasing attention for the representation of the causal knowledge especially useful in knowledge management. This paper proposes a model CRM critical success factor modelling and analysis based on fuzzy cognitive maps and using the paradigm of Computing with Words, in order to provide causal models easy to understand. To this end, the use of linguistic representation model based on linguistic 2-tuple in the competitive fuzzy cognitive maps is proposed, which allowing to perform the Computing with Words Processes without losing information. The main advantage of the model proposed for is that it allows increasing the interpretability of the causal models, being this fact knowledge management. Last, the paper presents a case study of the model proposed, as well as recommendations for future works.
Despite its usefulness and high impact there is shortcomings in knowledge based recommendation models. Among its limitations are lack of flexible models, the inclusion of linguistic information and the correct weighting of the factors involved for computing a global similarity. In this paper a new knowledge based recommendation models based on the 2-tuple linguistic representation model and OWA operators is presented. It includes data base construction, vector weights determination, client profiling, products filtering and recommendation generation. Its implementation make possible to improve reliability and interpretability in recommendations. And illustrative example is shown to demonstrate the model applicability.
A key goal of any engineering and software engineering in particular, is the quality of the final product. Software quality is often determined by the ability to meet the needs of customers and end users, as obtained as software requirements. To satisfy that needs is important a correct requirement engineering process in general, and a correct requirement prioritization in particular. Prioritizing software requirements is a complex decision making process. Traditional approaches do not perform aggregation of criteria with sufficient flexibility and adaptability to the specific contexts of organizations. In this paper we propose a requirements prioritization method that uses hierarchical aggregation process for information fusion. The proposal allows the inclusion of aspects such as the importance of the criteria and simultaneity. To demonstrate the applicability of the proposal a case study is developed. The paper ends with further work recommendations for extending the method.
Project interdependency modeling and analysis have has been ignored in project portfolio management. There are five types of project portfolio interdependencies: benefit, risk, outcome, schedule and resources. In the case of risks interdependencies a positive or negative correlation of risks occurs provoking risk diversification or amplification effects. In this work project portfolio risk interdependencies are modeled using the computing with word (CWW) paradigm. We propose a new method for modeling project portfolio interdependencies, and specially risks interdependencies, using the 2-tuples linguistic model and fuzzy cognitive maps. This proposal has many advantages for dealing with linguistic information making simpler the elicitation of knowledge from experts. Building a 2-tuple fuzzy cognitive map follows an approach more similar to human reasoning and the human decision making process. An illustrative example showed the applicability of the proposal. The paper ends with recommendation of future works that will concentrate on three objectives.
Analysis of critical success factors in software projects allow organizations to focus on the fundamentals factors to be successful in software development. In this paper a proposal for identifying and weighting critical success factors in software projects is shown. Focus Group and Analytic Hierarchy Process are used across the study. The proposal applicability is shown in a case in a data integration project. Re result shows the importance of client compromise among factors. Another important finding is the appropriateness and the applicability of the proposal. Paper ends with conclusion and future works recommendations.
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