Crowd Dynamics and Crowd Capital in Small Teams: Insights from three crowdsourcing exercises in higher education
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This dissertation focuses on collective forms or organizing that through crowds or communities undertake production or innovation activities. Such organizations deviate from the traditional notions of hierarchy, authority, and control; however, they are st ...
This article aims to study crowd dynamics in small teams. In particular we are specifically interested to internal crowdsourcing as a venue for innovation and new ideas production, questioning the difference with regard to other cooperative models based, e ...
In this paper, we provide guidelines for strategically using crowds as part of a crowdsourcing strategy and an open innovation portfolio. We start by defining crowd organisations as sustained through a crowd of loosely coupled and equally aligned agents th ...
Historically speaking, the notion of the type was reintroduced to the larger architectural discourse as a direct consequence of the crisis of the Modern. The task of revisiting the forms of the past also dictated the return of architectural methods that ha ...
Brightness has different meaning in different contexts and some of these are reviewed. The scientific definition of brightness does not represent our perception. The current definition is that from the IUPAC Gold Book and is mainly restricted to solutions. ...
This article aims to study “crowd” dynamics in small teams on the basis of the work presented in Tucci et al. [2016; 2017] and discussed below. Another goal of the study is to provide the setting for experiments in business domains to investigate how crowd ...
In this paper, we provide guidelines for strategically using crowds as part of a crowdsourcing strategy and an open innovation portfolio. We start by defining crowd organizations as sustained through a crowd of loosely coupled and mutually aligned agents t ...
This article aims to empirically study “crowd” dynamics in small teams and complement the work presented in Tucci et al. [2016], and Tucci and Viscusi [2017]. As in previous papers, we use as theoretical lens the framework and related typology of “crowd” d ...
Machine learning applications can benefit greatly from vast amounts of data, provided that reliable labels are available. Mobilizing crowds to annotate the unlabeled data is a common solution. Although the labels provided by the crowd are subjective and no ...