1,720,991 research outputs found
Handbook of Research on Multi-Agent Systems: Semantics and Dynamics of Organizational Models
No full textCollaboration and human factor as drivers for reputation system effectiveness
No full textReputation management is about evaluating an agent's actions and other agents' opinions about those actions, reporting on those actions and opinions, and reacting to that report thus creating a feedback loop. This social mechanism has been successfully used, through Reputation Management Systems (RMSs) to classify agents within normative systems. Most RMSs rely on the feedbacks given by the member of the social network in which the RMS itself operates. In this way, the reputation index can be seen as an endogenous and self produced indicator, created by the users for the users' benefit. This implies that users' participation and collaboration is a key factor for the effectiveness a RMS. In this work the above factor is explored by means of an agent based simulation, and is tested on a P2P network for file sharing. © 2010 Springer-Verlag
The propensity to innovate in a company: From theoretical models to case studies to simulation
No full textThe purpose of this paper is to delineate a set of useful variables able to show the level of propensity to innovate in a company. In order to evaluate innovation, the authors have built a model in which different variables that can help management to measure the level of innovation in their company are taken into consideration. The created model is based both on theories about innovation and on the authors' expertise. A questionnaire was put together by the authors with the aim of understanding the strength of the model and measures the level of innovation present in the company. The questionnaire was sent to 100 companies belonging to different Piedmont industries. © 2009 IEEE
Evaluation of human factor in reputation management systems, by means of agent-based simulation: Application to P2P networks
No full textCognitive biased action selection strategies for simulations of financial systems
No full textIn agent based simulations, the many entities involved usually deal with an action selection based on the reactive paradigm: they usually feature embedded strategies to be used according to the stimuli coming from the environment or other entities. This can give good results at an aggregate level, but in certain situations (e.g. Game Theory), cognitive agents, embedded with some learning technique, could give a better representation of the real system. The actors involved in real Social Systems have a local vision and usually can only see their own actions or neighbours' ones (bounded rationality) and sometimes they could be biased towards a particular behaviour, even if not optimal for a certain situation. In the paper, a method for cognitive action selection is formally introduced, keeping into consideration an individual bias: ego biased learning. It allows the agents to adapt their behaviour according to a payoff coming from the action they performed at time t-1, by converting an action pattern into a synthetic value, updated at each time, but keeping into account their individual preferences towards specific actions
La cultura di marketing nelle principali istituzioni che supportano le start-up innovative tech-based
No full textModeling cognitive distortions of behavioural finance
No full textBehavioural Finance (BF) is an approach for studying Finance and Economics, based on the interactions among cognitive sciences and decision-making models. Orthodox-Economic theory fails in representing the decisional process of individuals in a realistic way, especially regarding the non-rational component of their behavior. By moving beyond those approaches, which assume a completely rational behavior, BF explores the main cognitive distortions that could lead to sub-optimal decisions and behaviors. Traditional Finance considers non-rational behaviors like anomalies, but the effects observed in the real world indicate that new modellng efforts are required for the emotional components. This paper analyzes the most frequent behavioural distortions (biases, heuristics and framing effects) in terms of BF, and proposes their use within computational models, employed as tools for better understanding the aggregate and complex effects of emotionally distorted behaviors, as opposed to pure rational ones, when dealing with financial topics. © 2009 IEEE
Logistics and Agri‐Food: Digitization to Increase Competitive Advantage and Sustainability. Literature Review and the Case of Italy
No full textThis paper examines the current challenges faced by logistics with a focus on the agri‐food sector. After outlining the context, a review of the literature on the relationship between logistics and strategic management in gaining and increasing competitiveness in the agri‐food sector is con-ducted. In particular, the flow of the paper is as follows: after examining the aforementioned managerial problem and its broader repercussions, the paper proceeds to address two main research questions. First, how and by which tools can digitization contribute to improving supply chain management and sustainability in logistics? Second, what are the main managerial and strategic implications and consequences of this for the agri‐food sector in terms of efficiency, effectiveness, cost reduction, and supply chain optimization? Finally, the paper presents Italy as a case study, chosen both for its peculiar internal differences in logistical infrastructures and entrepreneurial management between Northern and Southern regions (which could be at least partially overcome with the use of new technologies and frameworks) and for the importance of the agri‐food sector for the domestic economy (accounting about 25% of the country’s GDP), on which digitization should have positive effects in terms of value creation and sustainability
Impact of process innovation on enterprise networks for competences exchange: E3, a multi agent based model
No full textA business process is a set of logically related tasks performed to achieve a defined business and related to improving organizational processes. A process innovation can happen at various levels: incremental way, redesign of existing processes, totally new processes. The knowledge behind a process innovation can be shared, acquired, changed and increased by the enterprises inside a network. An enterprise can decide to exploit the innovative process it owns, thus potentially gaining competitive advantage, but risking, in turn, that other players could reach the same technological level. Or it could decide to share it, in exchange for other competencies or money. These activities could be the basis for a network formation and/or impact the topology of an existing network, by changing the number and topology of ties and links. In the present work an agent based model is introduced (E3), that aims to explore how a process innovation can facilitate network formation of existing enterprises, affect the network topology (e.g.: an enterprise owning an innovative process could become a focal point), induce new players to enter the market and spread onto the network by being shared or internally acquired by new players
Impact of process innovation on enterprise networks for competences exchange: E3, a multi agent based model
No full textA business process is a set of logically related tasks performed to achieve a defined business and related to improving organizational processes. A process innovation can happen at various levels: incremental way, redesign of existing processes, totally new processes. The knowledge behind a process innovation can be shared, acquired, changed and increased by the enterprises inside a network. An enterprise can decide to exploit the innovative process it owns, thus potentially gaining competitive advantage, but risking, in turn, that other players could reach the same technological level. Or it could decide to share it, in exchange for other competencies or money. These activities could be the basis for a network formation and/or impact the topology of an existing network, by changing the number and topology of ties and links. In the present work an agent based model is introduced (E3), that aims to explore how a process innovation can facilitate network, formation of existing enterprises, affect the network topology (e.g.: an enterprise owning an innovative process could become a focal point), induce new players to enter the market and spread onto the network, by being shared or internally acquired by new players
- …
