Adapting question mapping as a methodology to help make sense of a community's collective wisdom and shared futures

2009 ◽  
Vol 19 (3) ◽  
pp. 367-385 ◽  
Author(s):  
Erna Gelles ◽  
Richard F. Ludeman
Keyword(s):  
Collective Wisdom ◽  
Shared Futures

Collective Wisdom

2019 ◽  
Author(s):  
William Uricchio ◽  
Katerina Cizek
Keyword(s):  
Collective Wisdom

Competition Policy for the New Era

2018 ◽  
Keyword(s):  
Developing Countries ◽  
Emerging Economies ◽  
Competition Policy ◽  
Competition Law ◽  
Critical Discussion ◽  
Industrialized Countries ◽  
Collective Wisdom ◽  
Brics Countries ◽  
Law And Policy ◽  
The World

This book presents a new stage in the contributions of the BRICS countries (Brazil, Russia, India, China, and South Africa) to the development of Competition Law and policy. These countries have significant influence in their respective regions and in the world. The changing global environment means greater political and economic role for the BRICS and other emerging countries. BRICS countries are expected to contribute nearly half of all global gross domestic product growth by 2020. For more than a century, the path of Competition Law has been defined by the developed and industrialized countries of the world. Much later, developing countries and emerging economies came on the scene. They experience many of the old competition problems, but they also experience new problems, and experience even the old problems differently. Where are the fora to talk about Competition Law and policy fit for developing and emerging economies? The contributors in this book are well-known academic and practising economists and lawyers from both developed and developing countries. The chapters begin with a brief introduction of the topic, followed by a critical discussion and a conclusion. Accordingly, each chapter is organized around a central argument made by its author(s) in relation to the issue or case study discussed. These arguments are thoughtful, precise, and very different from each another. Each chapter is written to be a valuable freestanding contribution to our collective wisdom. The set of case studies as a whole helps to build a collection of different perspectives on competition policy.

Collective wisdom

Lab on a Chip ◽  
2010 ◽  
Vol 10 (11) ◽  
pp. 1351 ◽  
Author(s):  
Holger Becker
Keyword(s):  
Collective Wisdom

Opportunities for Collective Wisdom in Stroke Research

1997 ◽  
Vol 7 (6) ◽  
pp. 313-314 ◽  
Author(s):  
Michael A. Moskowitz ◽  
Turgay Dalkara
Keyword(s):  
Collective Wisdom ◽  
Stroke Research

Knowledge Management: FROM THEORY TO PRACTICE

2012 ◽  
Vol 01 (11) ◽  
pp. 22-30
Author(s):  
Kamran Nazari ◽  
Mostafa Emami
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Critical Points ◽  
Organization Performance ◽  
Management Process ◽  
Dynamic Learning ◽  
Collective Wisdom ◽  
Theory To Practice ◽  
Wide Range ◽  
Peter Drucker

Knowledge management is a process that helps organizations to find important information, select, organize and publish them; and it’s a proficiency that will be necessary for actions like solving problems, dynamic learning, decision making. Knowledge management can improve a wide range of organization performance properties by enabling company to more intelligent performance, but it’s not enough alone; because knowledge management to be useful needs undertaking staff to organization and their job, that accept the knowledge management process with spirit and heart and perform it (Wiig, 1999:14).Knowledge management is the leveraging of collective wisdom to increase responsiveness and innovation. It is important that you discern from this definition three critical points. This definition implies that three criteria must be met before information can be considered knowledge. » Knowledge is connected. It exists in a collection (collective wisdom) of multiple experiences and perspectives Knowledge management is a catalyst. It is an action – leveraging. Knowledge is always relevant to environmental conditions, and stimulates action in response to these conditions. Information that does not precipitate action of some kind is not knowledge. In the words of Peter Drucker, ‘‘Knowledge for the most part exists only in application.’’ » Knowledge is applicable in un-encountered environments. Information becomes knowledge when it is used to address novel situations for which no direct precedent exists. Information that is merely ‘‘plugged in’’ to a previously encountered model is not knowledge and lacks innovation.

Financial fraud detection and big data analytics – implications on auditors’ use of fraud brainstorming session

2019 ◽  
Vol 34 (3) ◽  
pp. 324-337 ◽  
Author(s):  
Jiali Tang ◽  
Khondkar E. Karim
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Idea Generation ◽  
Fraud Detection ◽  
Content Type ◽  
Collective Wisdom ◽  
Fraud Risk ◽  
Collection Data ◽  
Audit Team

PurposeThis paper aims to discuss the application of Big Data analytics to the brainstorming session in the current auditing standards.Design/methodology/approachThe authors review the literature related to fraud, brainstorming sessions and Big Data, and propose a model that auditors can follow during the brainstorming sessions by applying Big Data analytics at different steps.FindingsThe existing audit practice aimed at identifying the fraud risk factors needs enhancement, due to the inefficient use of unstructured data. The brainstorming session provides a useful setting for such concern as it draws on collective wisdom and encourages idea generation. The integration of Big Data analytics into brainstorming can broaden the information size, strengthen the results from analytical procedures and facilitate auditors’ communication. In the model proposed, an audit team can use Big Data tools at every step of the brainstorming process, including initial data collection, data integration, fraud indicator identification, group meetings, conclusions and documentation.Originality/valueThe proposed model can both address the current issues contained in brainstorming (e.g. low-quality discussions and production blocking) and improve the overall effectiveness of fraud detection.

scholarly journals Social learning strategies regulate the wisdom and madness of interactive crowds

2018 ◽  
Author(s):  
Wataru Toyokawa ◽  
Andrew Whalen ◽  
Kevin N. Laland
Keyword(s):  
Social Learning ◽  
Learning Strategies ◽  
Group Size ◽  
Collective Intelligence ◽  
Collective Wisdom ◽  
The Social ◽  
Challenging Tasks ◽  
Task Uncertainty ◽  
The Individual ◽  
Social Learning Strategies

AbstractWhy groups of individuals sometimes exhibit collective ‘wisdom’ and other times maladaptive ‘herding’ is an enduring conundrum. Here we show that this apparent conflict is regulated by the social learning strategies deployed. We examined the patterns of human social learning through an interactive online experiment with 699 participants, varying both task uncertainty and group size, then used hierarchical Bayesian model-ftting to identify the individual learning strategies exhibited by participants. Challenging tasks elicit greater conformity amongst individuals, with rates of copying increasing with group size, leading to high probabilities of herding amongst large groups confronted with uncertainty. Conversely, the reduced social learning of small groups, and the greater probability that social information would be accurate for less-challenging tasks, generated ‘wisdom of the crowd’ effects in other circumstances. Our model-based approach provides evidence that the likelihood of collective intelligence versus herding can be predicted, resolving a longstanding puzzle in the literature.

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