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Carayannis, E., Ferreira, J., Jalali, M. & Ferreira, F. (2018). MCDA in knowledge-based economies: methodological developments and real world applications. Technological Forecasting and Social Change. 131, 1-3

E. G. Carayannis et al.,  "MCDA in knowledge-based economies: methodological developments and real world applications", in Technological Forecasting and Social Change, vol. 131, pp. 1-3, 2018

@article{carayannis2018_1732206009092,
	author = "Carayannis, E. and Ferreira, J. and Jalali, M. and Ferreira, F.",
	title = "MCDA in knowledge-based economies: methodological developments and real world applications",
	journal = "Technological Forecasting and Social Change",
	year = "2018",
	volume = "131",
	number = "",
	doi = "10.1016/j.techfore.2018.01.028",
	pages = "1-3",
	url = "https://www.sciencedirect.com/science/article/pii/S0040162518301306?via%3Dihub"
}

TY  - JOUR
TI  - MCDA in knowledge-based economies: methodological developments and real world applications
T2  - Technological Forecasting and Social Change
VL  - 131
AU  - Carayannis, E.
AU  - Ferreira, J.
AU  - Jalali, M.
AU  - Ferreira, F.
PY  - 2018
SP  - 1-3
SN  - 0040-1625
DO  - 10.1016/j.techfore.2018.01.028
UR  - https://www.sciencedirect.com/science/article/pii/S0040162518301306?via%3Dihub
AB  - 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.
ER  -