Intelligent and Complex Systems in Economics and Business

The objective of the article is to present the competitiveness of the federative entities in Mexico using a multicriteria analysis model based on composed indexes using ELECTRE III. The method considers a multicriteria decision support approach using expert preferences. The result is a model that allows the identification and ranking of the states in Mexico with the highest competitiveness rates. The limitations of the model are presented in the expert's cognitive effort to define the parameters of the ELECTRE III method. In addition, a multiobjective evolutionary algorithm for the generation of a total or partial pre-order is used. The findings are the ranking of the federative entities in Mexico compared with the competitiveness index by the Mexican Competitiveness Institute (IMCO for their acronym in Spanish).

In this paper, the notions of degree of global covering and degree of global redundancy on a fuzzy classification system are established and applied. Such notions are implemented in the evaluation of a fuzzy partition. In particular, the characterization of the financial solvency of an economic sector and the possible estimation of financial insolvency are considered as problems of fuzzy classification. The results of implementing fuzzy classification systems and global indices are illustrated on this application.

This work aims to model the alternatives of government incentives for promoting innovation with social impact. Firstly, it analyses the R&D performed by a small technological firm and, secondly, the subsequent production to enter the market done by a big producer. This two companies must agree on how to share the output; it is a game between these two players, with a bigger negotiation power held by the big producer. If the big company want a big share, the government could incorporate incentives through push and pull subsidies to compensate the small one. Each one of these strategies has advantages and limitations in its application, and consequently, this paper proposes to use hybrid contracts, where the government can articulate the advantages of both subsidies.

Market-driven product design decisions are receiving increasing attention in business practice, complemented by academic research on product design in a variety of disciplines. Mathematical and marketing research models are being integrated into decision-based design frameworks to represent customer behaviors and estimate the demand for design alternatives. The evolution of market structure eventually reshapes customer preference and competition, pushing the designers to rethink their design decision strategies. In this manner, it is necessary to develop decision support tools that would effectively provide support in new product design. In this paper, we argue that a combination of marketing decision support systems (MDSSs), multicriteria and multi-objective methodologies and agent technologies could be a very tool to support decision making in new product design applications. In this work, we propose a multi-agent architecture for a new product design MDSS and describe a system prototype for making new product design decisions.

The vertiginous development of technology and knowledge globalization has generated a high interest on social networks within organizations, where its presence has multiplied exponentially in recent years. That is why, it is proposed in this paper to analyze data extracted from social networks, specifically from Twitter, aiming to obtain different data elements that allow management and analysis of the opinions provided by users on different. This information is very useful for client management and acknowledging preferences of brands and organizations. In particular, this work responds to the following research questions: (1) How does the Twitter user behave in different brands? and (2) How do opinions on the network affect the company’s Twitter profile? In this manuscript, we present the tweet user profile for information analysis via a practical software architecture proposal, which is composed by four layers (extraction of the data source, ETL processes (extraction, transformation, and loading), selection of database, and visualization of the results). The implementation and dashboards of this architecture come from the study case of different types of organizations: banking, telephony, shopping, and supermarkets. The processing of the data corresponds to the extraction of tweets generated by the Twitter users of the organizations. Then, the ETL process is obtained via the useful Spoon from Pentaho Data Integration. The processed data is employed to build the final database, and finally, the generated information is visualized by utilizing dashboards from Qlik Sense Desktop. The results of this study evidence that it is possible to implement a practical architecture to analyze the model information of the Twitter user profile through dashboard; consequently, the organizations can opportunely realize better decisions.

Innovation has considered organizations’ competitive advantage. The purpose of this study is to visualize the effects of the behavior of innovation level at innovation capability change. This work presents a fuzzy controller design using logic tables and a generalized ordered weighted averaging (GOWA) index to model the internal innovation phenomenon of manufacturing enterprises in Morelia, Michoacán, Mexico. The linguistic rules were programmed using a fuzzy design module in MATLAB software, and the controller was simulated using the Simulink tool. The results show that the values of at least two inputs have to change in order for the innovation value to change, and two static input values are enough to restrict the minimum innovation value. This paper presents an original methodology for visualizing the behavior of the internal innovation of companies based on control and fuzzy set theory that allows us to capture the dynamics of the phenomenon.

Nowadays, the software environment has reached an unthinkable development in the world; companies in this area with the objective of competing aim to sustain software development and quality, influencing these two extents in the profitability of small and medium companies. Small- and medium-sized enterprises (SMEs) dedicated to software development are present in the software industry in Mexico and other countries, which is why they seek to improve their software development processes in order to offer quality services and products. This study has as main goal to evaluate the factorial structure and reliability of two extents: software quality and development, starting from measure and the factorial analysis of SMEs concept in the software area.

The growth of Mexican companies is measured by increasing sales, and some of their determinants are, according to the literature review, accounting and financial data such as total assets, financing alternatives, and profitability. We seek to know the weight of the evidence of each of the mentioned variables in order to identify if they are good predictors of growth. The applied methodology uses the weight of evidence and information value to rank variable importance. The most important variables are used to generate three different predictive models. Our results show that the main variables affecting growth are EBIT, consolidated net worth, and total assets. The best predictive model is artificial neural networks.

The objective of this article is to describe and elaborate a contextualization of how nowadays electronic leadership must become a strategic tool for organizations and since the beginning of the twenty-first century has evolved in a process of social influence mediated by Information and Communication Technologies, of such that it has come to produce changes in attitudes, feelings behaviors even in the performance of individuals within organizations. Modern leadership has had to adapt and learn to communicate with your work teams no longer traditionally face to face but through a communication mediated by different electronic elements from laptops, cell phones, tablets, and other items from anywhere in the world. The documentary methodology allowed us through the consultation of multiple documents and a broad contrast of the information to make a proposal that structures the leadership electronically and fundamentally the actions of leaders in virtualized environments such as those of today.

There is a data revolution in the agriculture that involves the analysis of this data, the development of new models and the application of these models in a practical and simple way. All new technologies allow to process big volumes of data with new mathematical algorithms, checking the information in real time, creating new value standards and changing the conception of agriculture. The aim of this chapter is to show some alternatives for the improvement of the crops using the big data, produced with the new technologies for massive sequencing in two specific examples: microbial massive analysis and molecular breeding.