La Responsabilité Sociale de l'Entreprise dans les très petites entreprises sénégalaises : quelles perceptions en ont les propriétaires-dirigeants ?

International audienceLa présente communication cherche à comprendre comment les propriétaires-dirigeants des Très Petites Entreprises (TPE) comprennent le concept de « Responsabilité Sociale de l'Entreprise » (RSE) et la perception qu'ils en ont. Nous nous positionnons sur l'opinion du propriétaire-dirigeant et tentons de montrer que la façon de percevoir la RSE peut revêtir des avis différents du fait de la confusion entretenue par les informations reçues de différents acteurs (chercheurs, praticiens, société civile) sur ce qu'est la RSE. Nous avons adopté une perspective cognitive en mettant en lumière les variables explicatives des perceptions de la RSE par les propriétaires-dirigeants des TPE étudiées. Nous nous sommes inspirés des travaux de Bazu et Pallasso (2008) et ceux de Cramer et al. (2006) pour qui le concept de « sense-making » appliqué à la RSE rend possible l'explication des particularités que l'on retrouve chez les propriétaires-dirigeants des TPE. Nos résultats ont permis de dire que malgré les contradictions théoriques qu'impliquent le concept « RSE », les propriétaires-dirigeants des TPE sont à la marge, mais conscients de toutes les discussions soulevées autour du concept. De manière pragmatique, ils forment et développent leurs propres modèles cognitifs, souvent indépendamment de la recherche académique. Cette étude souligne également une certaine déconnexion entre les universitaires et les praticiens de la RSE. L'étude a également confirmé l'importance, dans les TPE, des dimensions sociales et culturelles où les logiques non économiques sont considérées commegarantes d’une juste relation avec les différents acteurs. Ce qui inscrit la TPE dans des logiques durables et étaye l’opinion de la littérature scientifique selon laquelle il existe un lien étroit entre la RSE et la durabilité de l’entreprise

Prioritizing Tanzania’s agricultural development policy to build smallholder climate resilience. Final report for the Bill & Melinda Gates Foundation Grand Challenges Explorations 22: Risk-explicit and Evidence-based Policy Prioritization (REAP)

Faced with myriad options, Sub-Saharan Africa policy makers struggle to prioritize actions. Commonly used modeling approaches perform poorly in data scare conditions or focus intently on tools at hand. Policies, by consequence, report ‘wish lists’, making them a challenge to implement given resource constraints. Here, we evaluate the potential of using an alternative approach, Bayesian Networks (BNs), to prioritize agricultural policy actions, specifically modeling seven ‘Investment Areas’ listed in Tanzania’s Agriculture Sector Development Programme II

Intelligent modeling of e-Government initiatives in Greece

Over the last two years Greece has employed agile ICT solutions to reduce the administrative burden in front-office G2B transactions. This research supplements historic analysis with fuzzy cognitive maps to offer a multi-dimensional coupling of eGovernment initiatives with digital maturity assessment capabilities and a strategy alignment evaluation framework. This “intelligent x-ray” confirms that front-office technology is important in reducing administrative burden. The digital bypass of bureaucracy seems to be an effective start for Greece. However, this strategy can only serve as a short-term tactical choice. The “intelligent x-ray” provides executive level quantification and traceable reasoning to show that excessive emphasis on front- office technology will soon fail to support a strong eGovernment maturity. Organizational efficiency, interoperability, regulatory simplifications, and change management must also act as important objectives. Only then will ICT deliver its full potential, and the eGovernment maturity will improve significantly even with moderate ICT investments

Uma abordagem holística ao conceito de "smart city" com recurso a mapas cognitivos Fuzzy

O crescimento da população mundial é uma questão preocupante. As suas consequências podem ser dramáticas se as devidas medidas não forem tomadas. Esta preocupação levou à criação de "smart cities", que visam promover a melhoria da qualidade de vida dos cidadãos por meio da junção das novas tecnologias com a preservação do meio ambiente. Mas, para que essas cidades sejam realmente “smart”, é necessário avaliá-las – ou seja, é necessário compreender quais as áreas em que se deve intervir para tornar as cidades economicamente estáveis e ambientalmente sustentáveis. Nesse sentido, este estudo propõe o uso de mapas cognitivos fuzzy (FCMs) para analisar a dinâmica por detrás dos determinantes de uma smart city. Baseado em sessões intensivas de trabalho em grupo com um painel de especialistas em diferentes dimensões de uma smart city, o resultado é uma abordagem orientada para o processo, bem informada e que contém as características/componentes-chave que devem ser avaliadas neste tipo de cidade, nomeadamente: pessoas; planeamento e ambiente; tecnologia; infraestruturas e materiais; serviços; e transportes e mobilidade. A identificação destas componentes permitiu, assim, uma melhor compreensão das relações de causa-efeito existentes entre si e, consequentemente, estabelecer as bases para um melhor planeamento urbano por parte dos administradores municipais. Algumas das implicações práticas do estudo, assim como as vantagens e as limitações da abordagem proposta, são também apresentadas.The world’s rapidly growing population is an issue to be taken seriously. Its consequences could be dramatic if the required steps are not taken. Concerns about this problem have led to the creation of “smart” cities, which promote improvements in citizens’ quality of life through a combination of new technologies and environmentally sustainable practices. For these cities to be truly “smart”, they need to be evaluated in order to understand the areas in which interventions are necessary to make these cities economically stable and environmentally sustainable. Thus, this study proposed the use of fuzzy cognitive maps to analyze the dynamics behind smart cities’ components. Grounded in intensive group meetings with a panel of experts in different dimensions of these cities, the method applied produced a well-informed, process-oriented framework that contains the characteristics and/or components that should be assessed in this type of city. This result facilitates an improved understanding of smart cities’ cause-and-effect relationships and better strategic planning by urban planners and city administrators. The implications, advantages, and limitations of the proposed framework are also presented