Adaptive Governance for Attractive Smart City

  • Slimane ZaleneEmail author
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)


In his book entitled “le social et le vivant” J. FONTANET [1] explains that the multidimensional crisis of our societies is mainly due to a failure of our intelligence. This observation, dating back to the end of the 1970s, is still valid today because in the face of “complexity” we still continue to use mechanistic methods. From the one best way TAYLOR during the industrial revolution of the nineteenth century to the various best practices are required to fit into the post-industrial economy of the twentieth century, Enterprises have tried to adapt their management to the evolution of their environment. At the beginning of the twenty-first century, globalization and the digital economy required Enterprises to make intensive use of information and communication technologies and force them to constantly review their strategy to survive in a international market where performance is continually demanded. On one hand, to face a tough competition, and on the other hand, to respect multiple rules of QHSE (quality, hygiene, safety and environment), of sustainable development, of social responsibility … in a word of good governance in the most broad and not just limited to the company’s traditional stakeholders. In this context of management under several constraints, the artificial intelligence (AI) brings an additional dimension of adaptation to a self-adaptive management for good governance. In this regard, this paper first discusses the concept of systemic adaptation, then its application to business strategy, then the possibilities of using artificial intelligence to improve the many expected results of managers who are inundated with sometimes contradictory information with requests for decisions that are often urgent, and finally the broadening of this adaptive approach to make a smart city more attractive.


Identification Adaptation Flexibility and fractal methods 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Consultant en ManagementZéraldaAlgeria

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