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The purpose of this paper is to focus on the underpinning dynamics that explain collective intelligence.

Collective intelligence can be understood as the capacity of a collective system to evolve toward higher order complexity through networks of individual capacities. The authors observed two collective systems as examples of the dynamic processes of complex networks – the wiki course PeSO at the Universidad de Los Andes, Bogotá, Colombia, and an agent-based model inspired by wiki systems.

The results of the wiki course PeSO and the model are contrasted with a random network baseline model. Both the wiki course and the model show dynamics of accumulation, in which statistical properties of non-equilibrium networks appear.

The work is based on network science. The authors analyzed data from two kinds of networks: the wiki course PeSO and an agent-based model. Limitations due to the number of computations and complexity appeared when there was a high order of magnitude of agents.

Better understanding can allow for the measurement and design of systems based on collective intelligence.

The results show how collective intelligence emerges from cumulative dynamics.

The field of behavioral business ethics has come a long way since its inception nearly five decades ago. Pioneered in part in response to a number of high-profile corporate scandals, the early field of business ethics was thought by many to be a fad that would recede along with the salience of the scandals of the day. Yet, this could not have been further from the truth. The need for behavioral business ethics research remains ever-present, as evidenced by the sustained number of scandals and unethical behavior within and by organizations. Moreover, research in this area has burgeoned. In the 1980s, only 54 articles had been published on this topic (Tenbrunsel & Smith-Crowe, 2008); today, a similar search yields over 3,000 “hits.” In light of the area’s growth, we suggest the need to take a look back at the seminal work that sparked social scientific work in the field. In particular, this chapter has two main objectives. First, we provide a review of select foundational work. In so doing, we identify some of the key trends that characterized early knowledge development in the field. Second, we draw on this historical context to consider how past trends relate to current work and speak to future research opportunities.

The purpose of this paper is to explore, how organization theoretically diverse research on OCR is actually grounded, since insights into the organization theoretical foundations of OCR are completely lacking.

A selection of 85 articles on organizational change was made, published in top tier journals in 2010. The authors conducted a reference analysis based on 18 prominent organization theories and their main contributing authors.

The findings show firstly a very strong theoretical selectivity, focusing on cognitive, learning, and neo-institutional theories. Other theories are almost fully neglected. Secondly, this analysis suggests that current OCR struggles hard with transforming the cognitive frames of topical OT into fruitful accesses to the own object. The resulting theory application appears as a dissatisfying escape strategy, performed to cover theoretical antagonisms and to avoid a deeper confrontation with the underlying assumptions of OCR.

The authors are fully aware that the depth of their analysis is worth broadening. A more comparable scope in the amount of the theories, journals, articles, and of the covered time span would help to substantiate their results.

Pragmatic change approaches rely strongly on organizational change research. If OCR itself is not topical in terms of using available theoretical knowledge, pragmatic approaches fail to stand on solid ground. The paper therefore provides a background for the link between failing empirical change projects and the usage of available scientific knowledge.

An analysis of the organization theoretical topicality of organizational change research is completely missing. The paper therefore not only contributes to the discovery of a blind spot in organizational studies, it possibly helps to explore the reasons for the high percentage of failing change projects.