Measuring CMOT’s intellectual structure and its development

Meyer, Matthias; Zaggl, Michael A.; Carley, Kathleen M.

doi:10.1007/s10588-010-9076-0

Cited by 22 publications

(12 citation statements)

References 42 publications

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“…We considered the four years from 2010 to 2013. Since our interest lies in the management and organizational behavior literature, we screened the two simulation journals that have the closest ties with our Zou and Yilmaz (2011) discipline (Meyer et al 2009(Meyer et al , 2011: Computational and Mathematical Organization Theory and the Journal of Artificial Societies and Social Simulation. Then, we also screened articles published in a list of top management journals (based on ISI Thompson's Impact Factor) and decided to include the four presenting ABM-related publications (Table 1): Organization Science, Journal of Management Studies, Strategic Management Journal, and MIS Quarterly.…”

Section: Methodsmentioning

confidence: 99%

Controlling for false negatives in agent-based models: a review of power analysis in organizational research

Secchi

Seri

2016

Comput Math Organ Theory

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This article is concerned with the study of statistical power in agentbased modeling (ABM). After an overview of classic statistics theory on how to interpret Type-II error (whose occurrence is also referred to as a false negative) and power, the manuscript presents a study on ABM simulation articles published in management journals and other outlets likely to publish management and organizational research. Findings show that most studies are underpowered, with some being overpowered. After discussing the risks of under-and overpower, we present two formulas to approximate the number of simulation runs to reach an appropriate level of power. The study concludes with the importance for organizational behavior scholars to perform their models in an attempt to reach a power of 0.95 or higher at the 0.01 significance level.

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Section: Methodsmentioning

confidence: 99%

Controlling for false negatives in agent-based models: a review of power analysis in organizational research

Secchi

Seri

2016

Comput Math Organ Theory

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“…Following prior studies, to derive meaningful and unambiguous clusters, we set thresholds in the network that suppressed coincidental cocitations (Raasch et al, 2013) and excluded loosely connected publications (Small, 1980). In line with common practice (Babl, Schiereck, and Von Flotow, 2014;Meyer, Zaggl, and Carley, 2011), we evaluated the robustness of the network by gradually altering threshold levels for both link strength (L) and component size (C). 8 Our sensitivity analysis (Appendix 1) showed that the network structure is robust and that the selected thresholds of L > .45 and C > 3 allow for a good balance between size and number of individual clusters.…”

Section: Centrality and Cluster Analysismentioning

confidence: 99%

Reviewing the Field of External Knowledge Search for Innovation: Theoretical Underpinnings and Future (Re‐)search Directions

Ehls

Polier

Herstatt

2020

J of Product Innov Manag

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The field of external knowledge search for innovation has a long tradition and has inspired several schools of thought resulting in a rich and burgeoning body of research. However, the field suffers from two key limitations. First, the pluralism of research across multiple disciplines impedes our attention to the field as a whole, including its intellectual structure and core ideas. Second, recent developments in the business environment and key new ideas in the field complement taken-for-granted approaches and provide new opportunities for knowledge search. Based on a systematic co-citation analysis, we provide a reflective review of the literature and make several contributions. We integrate existing research across disciplines and offer a synthesis of a fragmented research landscape to present a global view of the field. Moreover, we propose a novel external search concept and introduce the idea of "decoupled search." Leveraging our synthesis and conceptualization further, we recommend future research directions for the entire field of external knowledge search for innovation. Practitioner Points • This article systematically integrates existing research across several disciplines and offers a synthesis of the field of external knowledge search for innovation.

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“…Some fields, such as social simulation, have a higher impact on other traditional disciplinary areas outside the social sciences (Squazzoni and Casnisi 2013). Additionally, subareas or social complexity show high degree of thematic and methodological and specialization (Meyer et al 2009(Meyer et al , 2011. This fragmentation eventually hinders the explanatory potential of the advances in these areas of study.…”

Section: Discussionmentioning

confidence: 99%

Self-organization and social science

Anzola

Barbrook-Johnson

Cano

2016

Comput Math Organ Theory

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Complexity science and its methodological applications have increased in popularity in social science during the last two decades. One key concept within complexity science is that of self-organization. Self-organization is used to refer to the emergence of stable patterns through autonomous and self-reinforcing dynamics at the micro-level. In spite of its potential relevance for the study of social dynamics, the articulation and use of the concept of self-organization has been kept within the boundaries of complexity science and links to and from mainstream social science are scarce. These links can be difficult to establish, even for researchers working in social complexity with a background in social science, because of the theoretical and conceptual diversity and fragmentation in traditional social science. This article is meant to serve as a first step in the process of overcoming this lack of cross-fertilization between complexity and mainstream social science. A systematic review of the concept of self-organization and a critical discussion of similar notions in mainstream social science is presented, in an effort to help practitioners within subareas of complexity science to identify literature from traditional social science that could potentially inform their research.

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Measuring CMOT’s intellectual structure and its development

Cited by 22 publications

References 42 publications

Controlling for false negatives in agent-based models: a review of power analysis in organizational research

Controlling for false negatives in agent-based models: a review of power analysis in organizational research

Reviewing the Field of External Knowledge Search for Innovation: Theoretical Underpinnings and Future (Re‐)search Directions

Self-organization and social science

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