Intelligence économique

Résumé

thumb|upright=1.9|Diagramme sur le système d'intelligence compétitive et technologique.L’intelligence économique est l'ensemble des activités coordonnées de collecte, de traitement et de diffusion de l'information utile aux acteurs économiques, en vue de son exploitation. On peut y ajouter les actions d'influence et de notoriété ainsi que celles liées à la protection de l'information. Elle se distingue de l’espionnage économique et/ou industriel car elle se pratique ouvertement et utilise uniquement des informations blanches ou grises obtenues par des moyens légaux. Le terme intelligence économique vient d'une traduction de l'expression anglaise competitive intelligence, mais il peut s'entendre plutôt dans sa double acception francophone (inter ligere, « faire le lien entre plusieurs éléments ») et anglophone (« renseignement »). Les spécialistes du domaine résument l'intelligence économique en un triptyque : veille (acquérir l'information stratégique pertinente), protection des info

Source officielle

https://fr.wikipedia.org/wiki/Intelligence_%C3%A9conomique

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Séances de cours associées (8)

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Early Requirements and Business-IT Alignment with SEAM for Business

Gil Regev, Irina Rychkova, Alain Wegmann

The early requirements of an IT system should be aligned with the organization’s business imperatives. To understand these imperatives it is necessary to understand the organization’s position within its environment. SEAM for Business is a method designed for analyzing the competitive environment of an organization, including its relationships with its customers, partners, and market regulators. From this analysis, the main requirements of the IT systems can be inferred. We illustrate the use of SEAM for Business with a real project aimed at redesigning the website of a consulting company.

IEEE2007

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Innovation and learning performance implications of free revealing and knowledge brokering in competing communities: insights from the Netflix Prize challenge

Christopher Tucci, Juan Andrei Villarroel Fernandez

Firms increasingly use open competitions to extend their innovation process and access new diverse knowledge. The Netflix Prize case we study in this paper is a multi-stage repeat-submission open competition involving the creation of new knowledge from across knowledge domains, a process which benefits from knowledge sharing across competing communities. The extant literature says little about the effects of different types and levels of knowledge sharing behavior on the learning and innovation outcomes of such a competitive system, or what the performance boundaries may be for the system as a result of such differences. Our research explores those boundaries unveiling important tradeoffs involving free revealing behavior-defined as voluntarily giving away codified knowledge and making it into a 'public good'aEuro"and knowledge brokering behavior-defined as using knowledge from one domain to innovate in another-on the learning performance of competing communities. The results, analyzing the system-level average and volatility of learning outcomes, lead to three conclusions: (i) greater knowledge sharing, as portrayed by greater free revealing and knowledge brokering, helps achieve better average learning for the system as a whole, however, (ii) achieving the best overall outcome possible from the system actually requires controlling the amount of knowledge brokering activity in the system. The results further suggest that (iii) it should not be possible to simultaneously achieve both the best overall outcome from the system and the best average learning for the system. The tradeoffs that ensue from these findings have important implications for innovation policy and management. This research contributes to practice by showing how it is possible to achieve different learning performance outcomes by managing the types and levels of knowledge sharing in open competitive systems.

Springer2013

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Innovation is one of the many challenges raised by the digitalization of business and economy. In the current competitive environment, businesses are characterized by radical transformations through digitalization of services and products and their ability to innovate is increasingly linked to the exploration and exploitation of information and communication technologies (ICTs). This paper investigates the role of information systems (IS) as a key factor to innovation capacity through an interpretative study of the IS innovation practices as well as perceptions by managers within a sample of 7 French based companies from various industries. The interviews have been conducted on the basis of a framework on IS innovation capacity maturity. Consistently with the framework, the interview guide addresses process areas and practices related to three core categories: management, innovation engineering, and support. The study reveals 7 fundamental contradictions that can explain the main tendencies observed across the companies, out of which the most striking is a generalized lack of maturity when it comes to exploiting their Information Systems to foster innovation.

Scitepress2016

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Innovation and learning performance implications of free revealing and knowledge brokering in competing communities: insights from the Netflix Prize challenge

Christopher Tucci, Juan Andrei Villarroel Fernandez

Springer2013