Guest editorial: Computational Intelligence in Business Administration

The International Conference on Modelling and Simulation in Engineering, Economics and Management (MS’10 Barcelona) was held at the University of Barcelona, Spain, 15–17 July, 2010. This special section of the Computer Science and Information Systems Journal entitled “Computational Intelligence in Business Administration” comprises extended versions of selected papers presented at the conference. In this edition of the conference more than 100 participants from more than 30 countries attended the conference with presentations concerning different topics of modelling and simulation in a wide range of areas including, economics, management, tourism, finance, engineering and mathematics.

In this section, eight papers have been selected for publication. All of them have gone a careful and rigorous review process. They have been selected based on their quality and their relation to the scope of the special section. The need for computational intelligence tools in business administration is becoming more relevant in the literature. Especially, because the real world demands more efficient models that permit to assess the information in a more complete way in order to maximize the benefits as much as possible. Business administration is a very broad area that encompasses many fundamental topics including management, finance, marketing and information systems. The selection of papers has also been conditioned by this aspect where we have tried to include papers from all the key subareas of business administration.

The first paper, by J. Rojas-Mora and J. Gil-Lafuente, introduces a new approach for reducing uncertainty in the resource selection problem by using fuzzy sets theory. They use triangular fuzzy numbers and weighted averages to assess the information. An application in marketing management is presented focused on market segmentation.

In the second paper, A.M. Gil-Lafuente and A. Klimova introduce a new framework for dealing with the theory of affinities in order to assess grouping problems. Several methodologies are used including fuzzy pretopology and Galois lattices. An application of this approach is developed in regional economic modelling concerning grouping methods in the Russian Federation and Ukraine.

Next paper, by Yejun Xu, Carlos Llopis-Albert and J. González, analyses the impact of Web 2.0 technologies in business performance. They find a connection through innovativeness. A case study in hospitality management is developed by using structural equation modelling in order to prove these propositions.

The fourth paper, by E. Edelhauser and A. Ionica, presents business intelligence software. It is developed with the aim of being very useful for Romanian companies during the economic crisis. It uses both qualitative and quantitative techniques and questionnaires. Several examples regarding the use of the software are also developed.

The fifth paper, by Jorge De Andrés, contributes to the research literature of fuzzy insurance analysis. He develops several methods for quantifying claim provisions of a non-life insurance company under fuzzy environments. He improves the ANOVA claim predicting model by using the expected value of a fuzzy number and other related techniques.

The next paper, by S.Z. Zeng, Leina Zheng, J.M. Merigó and Pan Tiejun, presents new aggregation operators based in uncertain environments that can be assessed with intuitionistic fuzzy information. They suggest a new aggregation operator that unifies the weighted average with the ordered weighted average by using intuitionistic fuzzy numbers. An application in a business decision making problem regarding the selection of optimal strategies is also presented.

Next, A. Terceño, M. Glòria Barberà-Mariné, H. Vigier and Y. Laumann study an application of fuzzy systems in finance. They analyse the stability of beta coefficients in portfolio management under uncertain environments that can be assessed with fuzzy regression models.

In the last paper, V. Georgescu suggests a new approach for propagating ontological and epistemic uncertainty by using risk assessment models and fuzzy time series techniques. Several computational intelligence tools are used in the analysis including probabilistic reasoning methods, fuzzy systems and neural networks.

As guest editors, we would like to express our gratitude to all the authors of accepted and rejected papers of this special section for their contributions and to the reviewers for their valuable effort in taking the time to review these papers and improve their quality by giving additional suggestions. Thanks goes also to the whole organizing team of the conference for a very pleasant event that has received considerable attention by many people. We would also like to thank Prof. Mirjana Ivanović, the editor-in chief of ComSIS, for her support during the preparation of this special section in the journal.

Guest Editor
José M. Merigó,
Manchester Business School,University of Manchester,
Booth Street West, M15 6PB Manchester, United Kingdom,

Guest Editor
Anna M. Gil-Lafuente,
Department of Business Administration, University of Barcelona,
Av. Diagonal 690, 08034 Barcelona, Spain