131 research outputs found

    Inter-Organizational Learning and Collective Memory in Small Firms Clusters: an Agent-Based Approach

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    Literature about Industrial Districts has largely emphasized the importance of both economic and social factors in determining the competitiveness of these particular firms\' clusters. For thirty years, the Industrial District productive and organizational model represented an alternative to the integrated model of fordist enterprise. Nowadays, the district model suffers from competitive gaps, largely due to the increase of competitive pressure of globalization. This work aims to analyze, through an agent-based simulation model, the influence of informal socio-cognitive coordination mechanisms on district\'s performances, in relation to different competitive scenarios. The agent-based simulation approach is particularly fit for this purpose as it is able to represent the Industrial District\'s complexity. Furthermore, it permits to develop dynamic analysis of district\'s performances according to different types of environment evolution. The results of this work question the widespread opinion that cooperative districts can answer to environmental changes more effectively that non-cooperative ones. In fact, the results of simulations show that, in the presence of turbulent scenarios, the best performer districts are those in which cooperation and competition, trust and opportunism balance out.Firm Networks, Collective Memory, Agent Based Models, Uncertainty

    Modelling Networked Cognition: A Socio-Computational Approach

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    In this paper an agent-based model is proposed in which effects of collective cognition are represented via the operazionalization of the construct of collective memory. The model is aimed at representing an evolving local networks of suppliers and final firms competing among them, making alliances and selling products on the market in the presence of environmental instability. A set of hypothesis has been tested in order to evaluate the influence on network’s performances of collective memory. Through the proposed model, this article illustrates advantages and limitations of computer based models to investigate collective cognition. The extent to which computational approaches can be used to model collective cognitive constructs such as collective memory and learning and their influence on social action is examined. Finally, implications for research and practice on organizational cognition resulting from a social computation view are outlined

    Human-Centered Design for Individual and Social Well-being: Editorial Preface

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    As digital technology use becomes widespread, its unintended consequences ranging from personal health to societal righteousness are under more scrutiny. Increasingly, digital designers are accused of not being considerate enough of the depth of their creations, and their impacts on our well-being. In this special issue, we explore an alternative, genuinely human-centered approach to technology design focusing on well-being and making our interactions with digital technology more meaningful, purposeful, and sustainable. To this end, the editorial starts with a brief review of the history of research that led to the growing field of digital well-being. We then introduce the Digital Well-being Design Framework, which goes beyond the ego-centric approach in human-centered design, and is multi-layered with self (intrapersonal), social (interpersonal), and transcendent (extra-personal) levels. Similar topics in related AIS journals are summarized, followed by the application of our framework to introduce and position the papers in this special issue. Our special issue aims to bring the topic of digital well-being to the forefront of the information systems research community and launch a new era of genuinely human-centered design

    UN ENFOQUE COGNITIVO DEL FHA PARA CORREGIR SESGOS EN EL JUICIO DE EXPERTOS: APLICACIÓN A UN CASO

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    El propósito de este trabajo es presentar un enfoque metodológico integrador que sirva de apoyo a la toma de decisiones. Hasta ahora la literatura científica ha producido principalmente trabajos de dos clases: análisis descriptivo, que se refiere a los procesos reales que caracterizan la valoración y selección de los individuos, y el análisis normativo, que analiza los procesos de selección realizados por individuos racionales idealizados. Entonces, cuando hablamos de un enfoque integrador, pretendemos desarrollar una metodología, que aun partiendo de instrumentos cuantitativos típicos del análisis normativo, tome también en consideración las implicancias cognitivo-comportamentales obtenidas por los especialistas en toma de decisión. Hemos desarrollado un modelo aplicativo basado en el análisis jerárquico fuzzy (FHA), en el que a las capacidades del proceso de jerarquía analítico (AHP) de racionalizar el proceso de decisión sin prescindir de las valoraciones, se añaden elementos de la teoría de conjuntos borrosos que permiten al decisor expresar la ambigüedad de su propia valoración. Este método corrige los juicios tomando en consideración los llamados sesgos cognitivos, es decir, distorsiones subjetivas relacionadas con la percepción de la utilidad y la incertidumbre. Por último, se ha llevado a cabo una experiencia para verificar el valor del modelo propuesto, los límites de su aplicabilidad y los posibles desarrollos futuros. Palabras clave: análisis jerárquico fuzzy, toma de decisión, enfoque cognitivo. Abstract This paper aims to propose a methodological integrated approach to support experts in decision making situation. Until now scientific literature has mainly produced works of two types: descriptive analysis, that talks about the real processes that characterize the evaluation and selection of individuals, and the normative analysis, that analyses the process of selection made by rational individuals. When we talk about an integrated approach, we try to develop a methodology, that even starting off of typical quantitative instruments of the normative analysis, also takes in consideration the cognitive side obtained by the specialists in decision making. We have developed an empirical model based on the fuzzy hierarchical analysis (FHA). In addition the capacities of Analytical Hierarchy Process (AHP) to rationalize the process of decision considering the evaluations, elements of the fuzzy set theory are considered in order to allow experts to express the ambiguity of their own evaluations. The proposed methodology corrects the judgments taking in consideration the so called cognitive biases, that is to say, subjective distortions related to the perception of utility and uncertainty. Finally, an experience has been carried out to verify the value of the proposed model, the limits of its applicability and possible future developments. Keywords: Fuzzy hierarchical analysis, Decision making, Cognitive approach

    Elegance as Complexity Reduction in Systems Design

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    Elegance is often invoked as a characteristic of good design, but it cannot be pursued as a design objective because of the absence of actionable definitions that can be translated into design strategies and metrics. In this work, we analyze elegance in the context of systems engineering using a perspective that integrates visual art, Gestalt psychology, neuroscience, and complexity theory. In particular, we measure elegance as effective complexity and theorize that it can be achieved by a process of complexity resolution based on the adoption of eight visual heuristics. We present an empirical study in which a sample of systems engineers were asked to assess alternative representations of a same system and show that effective complexity is strongly correlated to perceived elegance and systems effectiveness. Our results are consistent with independent findings obtained in other fields including design and psychology of perception showing that good design must embed an effective level of complexity achievable through a mix of familiarity and novelty

    Design for Multiplicity: Diving into the transdisciplinary nature of design processes

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    The contributions in this issue, selected from the ones presented at the DFGN.R 2023, a two-day event hosted at the METU Design Factory in Ankara, Turkey, and organized by the Design Factory Global Network, represent a broad cross-section encompassing various fields such as phenomenology, social theory, psychology, philosophy, artificial intelligence, and art, resonating with the principles of 21st Century learning and the United Nations’ Sustainable Development Goals, supporting the changing expectations of academics in producing alternative research outcomes in collaborative, practice-based research. These contributions offer valuable insights into how designers and innovators navigate the ever-expanding landscape of challenges and opportunities in multiple fields, elevating pedagogy and enhancing the art and science of learning, thinking, and doing

    A gap analysis of Regional Innovation Systems (RIS) with medium-low innovative capabilities: the case of Campania Region (Italy)

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    The aim of this paper is to investigate the implementation of a Regional Innovation System (RIS) in the Campania Region, an Italian Region characterized by a medium-low innovation capability. The paper focuses on a comparative analysis using the data of the Regional Innovation Scoreboard 2009 and the data about services provided by the most innovative Italian Regions. The paper states that low performances of Campania Region Innovation System (CRIS) are due to the lack of actors that act as Catalysts between researchers, which play the role of Explorers of knowledge, and entrepreneurs, which play the role of Exploiters. Furthermore, the paper suggests that it is necessary a strong action of the Regional policy maker (the Governor) to build an effective environment where such Catalysts can effectively develop. To this aim the local Regional government should establish an Agency for Innovation, which acts as a Governor to promote the birth and the growth of new actors and of new competencies needed to complete the CRIS

    Socially-augmented argumentation tools: rationale, design and evaluation of a debate dashboard

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    Collaborative Computer-Supported Argument Visualization (CCSAV) is a technical methodology that offers support for online collective deliberation over complex dilemmas. As compared with more traditional conversational technologies, like wikis and forums, CCSAV is designed to promote more critical thinking and evidence-based reasoning, by using representations that highlight conceptual relationships between contributions, and through computational analytics that assess the structural integrity of the network. However, to date, CCSAV tools have achieved adoption primarily in small-scale educational contexts, and only to a limited degree in real world applications. We hypothesise that by reifying conversations as logical maps to address the shortcomings of chronological streams, CCSAV tools underestimate the importance of participation and interaction in enhancing collaborative knowledge-building. We argue, therefore, that CCSAV platforms should be socially augmented in order to improve their mediation capability. Drawing on Clark and Brennan’s influential Common Ground theory, we designed a Debate Dashboard, which augmented a CCSAV tool with a set of widgets that deliver meta-information about participants and the interaction process. An empirical study simulating a moderately sized collective deliberation scenario provides evidence that this experimental version outperformed the control version on a range of indicators, including usability, mutual understanding, quality of perceived collaboration, and accuracy of individual decisions. No evidence was found that the addition of the Debate Dashboard impeded the quality of the argumentation or the richness of content
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