Robust modeling of human contact networks across different scales and proximity-sensing techniques

The problem of mapping human close-range proximity networks has been tackled using a variety of technical approaches. Wearable electronic devices, in particular, have proven to be particularly successful in a variety of settings relevant for research in social science, complex networks and infectious diseases dynamics. Each device and technology used for proximity sensing (e.g., RFIDs, Bluetooth, low-power radio or infrared communication, etc.) comes with specific biases on the close-range relations it records. Hence it is important to assess which statistical features of the empirical proximity networks are robust across different measurement techniques, and which modeling frameworks generalize well across empirical data. Here we compare time-resolved proximity networks recorded in different experimental settings and show that some important statistical features are robust across all settings considered. The observed universality calls for a simplified modeling approach. We show that one such simple model is indeed able to reproduce the main statistical distributions characterizing the empirical temporal networks

Gender homophily from spatial behavior in a primary school: a sociometric study

We investigate gender homophily in the spatial proximity of children (6 to 12 years old) in a French primary school, using time-resolved data on face-to-face proximity recorded by means of wearable sensors. For strong ties, i.e., for pairs of children who interact more than a defined threshold, we find statistical evidence of gender preference that increases with grade. For weak ties, conversely, gender homophily is negatively correlated with grade for girls, and positively correlated with grade for boys. This different evolution with grade of weak and strong ties exposes a contrasted picture of gender homophily

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

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

Common Territory? : Comparing the IMP Approach with Economic Geography

The IMP research tradition has always been open to the cross-fertilisation of ideas with other social science disciplines that study similar phenomena. Recent years have seen a growing interest among IMP researchers in phenomena such as regional strategic networks, spatial clusters and innovation and new business development in networks. IMP papers published on these topics are increasingly citing conceptual frameworks and empirical findings from the field of economic geography. This paper discusses the development of IMP thought and the development of thought in economic geography (particularly evolutionary economic geography), and compares their approaches to the analysis of regional phenomena. The goal is to identify key ideas from economic geography that have been under-exploited in IMP research, in order to suggest original new approaches available to IMP researchers interested in these fields. A number of such ideas are explored: proximity as a multi-dimensional and multi-faceted concept; the distinction between, and relative importance of, learning activities arising automatically from being embedded in a community (local or regional buzz) and learning activities arising from positive investment in channels of communication (pipelines); the concept of relational capital developed by economic geographers; and, conceptualisations of externalities commonly used in the study of spatial clustersPeer reviewedFinal Accepted Versio

Sensing, Understanding, and Shaping Social Behavior

The ability to understand social systems through the aid of computational tools is central to the emerging field of computational social systems. Such understanding can answer epistemological questions on human behavior in a data-driven manner, and provide prescriptive guidelines for persuading humans to undertake certain actions in real-world social scenarios. The growing number of works in this subfield has the potential to impact multiple walks of human life including health, wellness, productivity, mobility, transportation, education, shopping, and sustenance. The contribution of this paper is twofold. First, we provide a functional survey of recent advances in sensing, understanding, and shaping human behavior, focusing on real-world behavior of users as measured using passive sensors. Second, we present a case study on how trust, which is an important building block of computational social systems, can be quantified, sensed, and applied to shape human behavior. Our findings suggest that:1) trust can be operationalized and predicted via computational methods (passive sensing and network analysis) and 2) trust has a significant impact on social persuasion; in fact, it was found to be significantly more effective than the closeness of ties in determining the amount of behavior change.U.S. Army Research Laboratory (Cooperative Agreement W911NF-09-2-0053

Boundaryless Management - Creating, transforming and using knowledge in inter-organizational collaboration. A literature review

Current literature on organizations often argues that firms are becoming increasingly dependent on knowledge residing outside their own boundaries requiring organizations to increase their entrepreneurial abilities and make their boundaries more flexible and permeable. This paper reviews the literature on what might be called interorganizational knowledge work. Implied in this focus is an assumption of clear organizaitonal boundaries. Rather than taking these boundaries and their importance for granted, the current review, however, aims at relativizing these boundaries. By focusing the empirical phenomenon of collaboration between individuals in different organizations, four different streams of literature with different constructions of the organizational boundary and its importance were identified: the literature on learning in alliances and joint ventures, the literature on collaboration in industrial networks, the literature on social networks and communities of practice and finally the literature on geographical clusters and innovation systems. The above four streams of the literature are reviewed with a special focus on the following three questions: 1. What is the role of (organizational) boundaries in interorganizational knowledge work? 2. What do we know about how these boundaries can be overcome? 3. What are the implications for managing interorganizational knowledge work spelled out in the literature?Interorganizational collaboration; Knowledge Management; Literature review