Journal of Information Systems Engineering and Management

Journal of Information Systems Engineering and Management, 2020 - Volume 5 Issue 3, Article No: em0120
https://doi.org/10.29333/jisem/8428

Published Online: 30 Jul 2020

Views: 1474 | Downloads: 1926

The paper discusses the role of integrating Artificial Intelligence (AI) and Data Science (DS) with the strategic foresight. That is, combining the art of conjecture with several algorithms available in the literature. The combination between qualitative and quantitative methods offers a new dynamic adaptation route to face the rapidly changing environment, to make strategic design more flexible in the long term. The proposal uses the ISSM framework as a notion of a Strategic Early Warning System (SEWS). Thus, an ISSM framework could assist organizations during the transition from dealing with discontinuities or strategic surprises to a new normal, using new capacities to creating knowledge of futures. The purpose is help to develop the component named competitive intelligence (CI) architecture to create knowledge about the future, improving continuous learning, and promote the capacity to adaptation. Therefore, anticipation, learning and strategic adaptation, are key attributes for building strategic flexibility that responds to several challenges.

strategic foresight artificial intelligence data science early warning system dynamic analysis

• Ackoff, R. L. (1981). Creating the Corporate Future. John Wiley & Sons, Philadelphia.
• Agami, N., Atiya, A., Saleh, M. and El-Shishiny, H. (2009). A neural network based dynamic forecasting model for Trend Impact Analysis. Technological Forecasting and Social Change, 76(7), 952-962. https://doi.org/10.1016/j.techfore.2008.12.004
• Agami, N., Omran, A., Saleh, M. and El-Shishiny, H. (2008). An enhanced approach for trend impact analysis. Technological forecasting and social change, 75(9), 1439-1450. https://doi.org/10.1016/j.techfore.2008.03.006
• Agami, N., Saleh, M. and El-Shishiny, H. (2010). A fuzzy logic based trend impact analysis method. Technological Forecasting and Social Change, 77(7), 1051-1060. https://doi.org/10.1016/j.techfore.2010.04.009
• Amer, M., Daim, T. and Jetter, A. (2013). A review of scenario planning. Futures, 26, 23-40. https://doi.org/10.1016/j.futures.2012.10.003
• Ansoff, H. I. (1975). Managing Strategic Suprise by Response to Weak Signals. California. Management Review, XVIII(2), 21-33. https://doi.org/10.2307/41164635
• Bachelard, G. (1936). Le Surrationalisme, dans Inquisitions [revue], repris dans tudes. Paris.
• Bachelard, G. (1949). Le Rationalisme appliqu. Paris 3, france: Presses Universitaires.
• Barlow, H. B. (1989). Unsupervised learning. Neural computation, 1(3), 295-311. https://doi.org/10.1162/neco.1989.1.3.295
• Bekey, G. A. and Kogan, B. J. (Eds.). (2012). Modeling and simulation: Theory and practice: A memorial volume for professor Walter J. Karplus (1927–2001). Springer Science & Business Media.
• Berger, G. (1957). Sciences humaines et prévision. Revue des Deux Mondes, 1829-1971, 417-426.
• Cabezas, R. T. and Verdegay, J. L. (2019, June). Intelligent System of Strategic Monitoring. In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1-6). IEEE. https://doi.org/10.23919/CISTI.2019.8760643
• Calof, J. (2015). Creating impactful intelligence: Communication lessons from the corporate environment. In Intelligence Communication in the Digital Era: Transforming Security, Defence and Business (pp. 72-87). Palgrave Pivot, London. https://doi.org/10.1057/9781137523792_6
• Calof, J., Arcos, R. and Sewdass, N. (2018). Competitive intelligence practices of European firms. Technology Analysis & Strategic Management, 30(6), 658-671. https://doi.org/10.1080/09537325.2017.1337890
• Calof, J., Richards, G. and Smith, J. (2015). Foresight, competitive intelligence and business analytics—tools for making industrial programmes more efficient. Foresight, 9(1 (eng)). https://doi.org/10.17323/1995-459X.2015.1.68.81
• Carlsson, C. and Fullér, R. (1996, October). Adaptive fuzzy cognitive maps for hyperknowledge representation in strategy formation process. In Procs. of the Int’l Panel Conf. on Soft and Intelligent Comp. (43-50).
• De Jouvenel, B. (1967). Arte della congettura. Florencia: Vallecchi Editore.
• Díaz‐Fernández, M. C., González‐Rodríguez, M. R. and Simonetti, B. (2019). The moderating role of top management team diversity in strategic change in a multicultural context. European Management Review, 16(4), 957-973. https://doi.org/10.1111/emre.12306
• Dickerson, J. and Kosko, B. (1994). Virtual worlds as fuzzy cognitive maps. Presence: Teleoperators & Virtual Environments, 3(2), 173-189. https://doi.org/10.1162/pres.1994.3.2.173
• Dzutsati, V. (2019). An Agent-Based Model of Corruption: Micro Approach (version 1.1.0). Retrieved October 5, 2019 from the Computational Model Library: https://www.comses.net/codebases/4520/releases/1.1.0/
• Fernández, Y., Cruz, C. and Verdegay, J. L. (2018). A new model based on soft computing for evaluation and selection of software products. IEEE Latin America Transactions, 16(4), 1186-1192. https://doi.org/10.1109/TLA.2018.8362155
• Forrester, J. W. (1970). Urban dynamics. IMR; Industrial Management Review (Pre-1986), 11(3), 67.
• Ghifary, M., Kleijn, W. B., Zhang, M., Balduzzi, D. and Li, W. (2016, October). Deep reconstruction-classification networks for unsupervised domain adaptation. In European Conference on Computer Vision (pp. 597-613). Springer, Cham. https://doi.org/10.1007/978-3-319-46493-0_36
• Gilad, B. (2006). Strategic Early Warning. Competitive Intelligence Magazine, 9(2), 14-17
• Goal QPC (2019). Retrieved November 15, 2019 from the GOAL QPC. Memory Jogger. https://goalqpc.com
• Godet, M. (1995a). Estrategia y gestión competitiva, de la anticipación de la acción: manual de prospectiva y estrategia. (Alfaomega, Ed.).
• Godet, M. and Roubelat, F. (1996). Creating the future: the use and misuse of scenarios. Long Range Plan, 29(2), 164-171. https://doi.org/10.1016/0024-6301(96)00004-0
• Gordon, T. and Hayward, H. (1968). Initial experiments with the cross impact matrix method of forecasting. Futures, 1(2), 100-116. https://doi.org/10.1016/S0016-3287(68)80003-5
• Gordon, T., Becker, H. and Gerjuoy, H. (1974). Trend impact analysis: anew forecasting tool. Futures Group.
• Husserl, E. (1931). Méditations cartésiennes: introduction à la phénoménologie.
• Husserl, E. (1936). HuDie Krisis der europe aischen Wissenschaften und die tranzendentale Pheanomenologie. Eine Einleitung in die phe anomenologische Philosophie. W. Biemel (hrsg), 2, 77–176.
• Kosko, B. (1986a). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24(1), 65-75. https://doi.org/10.1016/S0020-7373(86)80040-2
• Kosko, B. (1986b). Fuzzy knowledge combination. International Journal of Intelligent Systems, 1(4), 293-320. https://doi.org/10.1002/int.4550010405
• Koyré, A. (1928). La philosophie de Jacob Boehme. Paris 3.
• Koyré, A. (1940). Du Monde Clos √† l’Univers Infini. Paris: √âtudes Galil√©ennes, Hermann.
• Leder, H (2010). Primary source intelligence in a collection plan. Retrieved from the SCIP – Strategic & Competitive Intelligence Professionals: https://www.scip.org
• Marcel, G. (1926). Journal métaphysique, 10.
• Marcel, G. and Segond, J. (1935). Être et avoir. Les Études philosophiques, 9(1/2), 48-53.
• Meadows, D. H. (1989). System dynamics meets the press. System Dynamics Review, 5(1), 69-80. https://doi.org/10.1002/sdr.4260050106
• Ratzé, C., Gillet, F., Müller, J. P. and Stoffel, K. (2007). Simulation modelling of ecological hierarchies in constructive dynamical systems. Ecological complexity, 4(1-2), 13-25. https://doi.org/10.1016/j.ecocom.2007.02.014
• Raynor, M. E. (2004). Strategic Flexibility: Taking the Fork in the Road. Competitive Intelligence Magazine, 7(1), 6-13.
• Reinhardt, W. A. (1984). An early warning system for strategic planning. Long Range Planning, 17(5), 25-34. https://doi.org/10.1016/0024-6301(84)90034-7
• Schwarz, J. O. (2005). Pitfalls in implementing a strategic early warning system. Foresight.
• Schwarz, J. O. (2009). „Schwache Signale “in Unternehmen: Irrtümer, Irritationen und Innovationen. In Zukunftsforschung und Zukunftsgestaltung (pp. 245-254). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78564-4_18
• Škulj, J. (2012). Complexity, Literature, Sciences: Initial Remarks on Discourse and Dialogue. Primerjalna književnost, 35(2).
• Slaughter, R. (1988). Recovering the future. Melbourne, VIC: Graduate School of Environmental Science, Monash University.
• Trujillo-Cabezas, R. (2008). El campo de los estudios de futuro: Contrastación entre el foresight y la prospectiva. Bogotá: Convenio Andrés Bello - Universidad Externado de Colombia.
• Trujillo-Cabezas, R. (2020). Towards the development of future trend scenarios through dynamic analysis: A proposal of integration of Artificial Intelligence, Data Sciences and the field of Futures Studies to adapt to new environments. 2020 15th Iberian Conference on Information Systems and Technologies (CISTI), Sevilla, Spain, pp. 1-6. https://doi.org/10.23919/CISTI49556.2020.9140880
• Trujillo-Cabezas, R. and Verdegay, J. L. (2019). Integrating Soft Computing into Strategic Foresight Methods: Towards an Adaptive Learning Environment Supported by Futures Studies (Vol. 387). Springer Nature. https://doi.org/10.1007/978-3-030-25432-2
• Trujillo-Cabezas, R. and Verdegay, J. L. (2020). Modeling and Simulation of the Future. In Integrating Soft Computing into Strategic Foresight Methods (pp. 113-147). Springer, Cham. https://doi.org/10.1007/978-3-030-25432-2_5
• Trujillo-Cabezas, R. and Verdegay, J. L. (2020). Strategic Foresight: Definitions and Key Concepts. In Integrating Soft Computing into Strategic Foresight Methods (pp. 29-41). Springer, Cham. https://doi.org/10.1007/978-3-030-25432-2_2
• Turner, M. A. (2005). Why secret intelligence fails. Potomac Books, Inc.
• Yang, L., Xu, C. and Wan, G. (2019). Exploring the impact of TMTs’ overseas experiences on innovation performance of Chinese enterprises. Chinese Management Studies, 13(4), 1044-1085. https://doi.org/10.1108/CMS-12-2018-0791

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.