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- Developing a socio-technical evaluation index for tourist destination competitiveness using cognitive mapping and MCDAPublication . Carayannis, Elias G.; Ferreira, Fernando A. F.; Bento, Paulo; Ferreira, João José de Matos; Jalali, Marjan; Fernandes, Bernardo M.Q.The tourism sector has experienced remarkable growth over the past few years. Its relevance to the economy of a wide range of countries has made it the subject of analysis of researchers and tourist destination managers alike; in part, due to the increasing competition among tourist destinations. Interest has thus emerged in the design, development and application of methodologies that might allow the competitiveness of tourist destinations to be evaluated. Notwithstanding, many studies reveal shortfalls with regard to the definition and weighting of evaluation criteria. By combining knowledge- and experience-based techniques (i.e. cognitive mapping and the measuring attractiveness by a categorical based evaluation technique (MACBETH)), this study follows a socio-technical approach, aiming to create a consistent evaluation index for tourist destinations, as a measure of their competitiveness. Grounded on a real-world application, the results were validated both by a panel of experts and the head of one of the largest travel agencies operating in Portugal, and show that cognitive mapping allows the cause-and-effect relationships between determinants of tourist destination competitiveness to be better understood, while MACBETH introduces realism into the calculation of the respective trade-offs. The limitations and managerial implications of the system created are also discussed.
- MCDA in knowledge-based economies: Methodological developments and real world applicationsPublication . Carayannis, Elias G.; Ferreira, João; Jalali, Marjan; Ferreira, Fernando A. F.The importance of knowledge in creating value, driving productivity and promoting economic growth has long been recognized. Accompanying this recognition of the central role of knowledge in today's economies has been an added focus on information technology, learning and the accelerated pace of technical and scientific advance that results therefrom. Closely connected to these developments has been the advent of big data; and as information becomes available at greater volumes and higher speed, the focus is shifting from quantity to the quality of the information collected and the manner in which it is used. In this respect, Multiple Criteria Decision Analysis (MCDA) techniques constitute valuable tools for structuring and evaluating complex decision situations, and can allow for more informed, potentially better decisions. MCDA techniques are able to build on the knowledge of expert participants in a given field, and produce assessment systems based on values and experience. Constructivist in nature, this approach has grown exponentially over the past few decades, causing a change in the decision-making arena in general, and in the field of decision support systems (DSS) in particular. The objective of this special issue is to bring together recent developments and methodological contributions within MCDA, with the challenges which characterize the knowledge-based economy, as they pertain to the themes of technological forecasting and social change.