Tacit Knowledge Network Development: The Comparative Analysis of Knowledge Threads in Complex Systems

2010 ◽  
Author(s):  
Susu Nousala ◽  
Suthida Jamsai-Whyte ◽  
William P. Hall
Keyword(s):  
Comparative Analysis ◽  
Complex Systems ◽  
Tacit Knowledge ◽  
Knowledge Network ◽  
Network Development ◽  
Analysis Of Knowledge

scholarly journals The use of Qualitative Comparative Analysis (QCA) to address causality in complex systems: a systematic review of research on public health interventions

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Benjamin Hanckel ◽  
Mark Petticrew ◽  
James Thomas ◽  
Judith Green
Keyword(s):  
Public Health ◽  
Comparative Analysis ◽  
Complex Systems ◽  
Qualitative Comparative Analysis ◽  
Complex Interventions ◽  
Health Interventions ◽  
Data Availability ◽  
Future Research ◽  
Public Health Interventions ◽  
Minimum Criteria

Abstract Background Qualitative Comparative Analysis (QCA) is a method for identifying the configurations of conditions that lead to specific outcomes. Given its potential for providing evidence of causality in complex systems, QCA is increasingly used in evaluative research to examine the uptake or impacts of public health interventions. We map this emerging field, assessing the strengths and weaknesses of QCA approaches identified in published studies, and identify implications for future research and reporting. Methods PubMed, Scopus and Web of Science were systematically searched for peer-reviewed studies published in English up to December 2019 that had used QCA methods to identify the conditions associated with the uptake and/or effectiveness of interventions for public health. Data relating to the interventions studied (settings/level of intervention/populations), methods (type of QCA, case level, source of data, other methods used) and reported strengths and weaknesses of QCA were extracted and synthesised narratively. Results The search identified 1384 papers, of which 27 (describing 26 studies) met the inclusion criteria. Interventions evaluated ranged across: nutrition/obesity (n = 8); physical activity (n = 4); health inequalities (n = 3); mental health (n = 2); community engagement (n = 3); chronic condition management (n = 3); vaccine adoption or implementation (n = 2); programme implementation (n = 3); breastfeeding (n = 2), and general population health (n = 1). The majority of studies (n = 24) were of interventions solely or predominantly in high income countries. Key strengths reported were that QCA provides a method for addressing causal complexity; and that it provides a systematic approach for understanding the mechanisms at work in implementation across contexts. Weaknesses reported related to data availability limitations, especially on ineffective interventions. The majority of papers demonstrated good knowledge of cases, and justification of case selection, but other criteria of methodological quality were less comprehensively met. Conclusion QCA is a promising approach for addressing the role of context in complex interventions, and for identifying causal configurations of conditions that predict implementation and/or outcomes when there is sufficiently detailed understanding of a series of comparable cases. As the use of QCA in evaluative health research increases, there may be a need to develop advice for public health researchers and journals on minimum criteria for quality and reporting.

scholarly journals Model of the Process of Conducting Computer Attacks Using Special Information Influences

2021 ◽  
pp. 12-20
Author(s):  
Sergey Kondakov ◽  
◽  
Ilya Rud ◽  
Keyword(s):  
Information Systems ◽  
Comparative Analysis ◽  
Complex Systems ◽  
Research Method ◽  
System Analysis ◽  
Level Of Abstraction ◽  
Proposed Model ◽  
Analysis And Synthesis ◽  
Computer Attacks ◽  
Special Information

Purpose of work: development of a model of the process of conducting a computer attack. Research method: theory of complex systems, comparative analysis within the framework of system analysis and synthesis. Result: it is shown that the application of the proposed model of the process of conducting computer attacks allows you to fully describe the process, taking into account its inherent features and characteristics. The use in the model of information from the MITRE ATTACK database of Mitre, which contains a description of the tactics, techniques and methods used by cybercriminals, allows you to reduce the level of abstraction and describe specific scenarios for conducting complex targeted computer attacks with the maximum approximation to practice. The developed model is supposed to be used to form scenarios of computer attacks when assessing the security of information systems.

Reality based scenarios facilitate knowledge network development

1995 ◽  
Vol 4 (1) ◽  
pp. 16-21 ◽  
Author(s):  
Judith Manning ◽  
Veronica Broughton ◽  
Edwina A. McConnell
Keyword(s):  
Knowledge Network ◽  
Network Development

Enabling organizations to implement smarter, customized social computing platforms by leveraging knowledge flow patterns

2015 ◽  
Vol 19 (1) ◽  
pp. 95-107 ◽  
Author(s):  
Ramesh Chandra ◽  
Reethika S Iyer ◽  
Ramakrishnan Raman
Keyword(s):  
Knowledge Sharing ◽  
Tacit Knowledge ◽  
Social Computing ◽  
Flow Patterns ◽  
Knowledge Network ◽  
Knowledge Flow ◽  
Knowledge Sourcing ◽  
Content Type ◽  
Computing Platforms ◽  
The Impact

Purpose – The purpose of this study was to understand the knowledge sharing in projects based on knowledge flow patterns. The impact of attrition, thereby leading to a loss of tacit knowledge, inability to capture and reuse knowledge and inability to understand the knowledge flow patterns, which leads to lack of structured workspace collaboration, are frequently faced challenges in organizations. The change in knowledge sourcing behaviors by the current generation workforce has a high reaching impact in driving collaboration among employees. Design/methodology/approach – This paper attempts to study this impact and identify means to improve the effectiveness of collective knowledge sharing via social computing platforms. As part of this study, customized solutions are devised based on knowledge flow patterns prevalent in teams. Knowledge network analysis (KNA), a socio-metric analysis, is performed to understand knowledge flow patterns among employees in a team which helps understand the relationships between team members with respect to knowledge sharing. KNA helps in understanding ties and interactions between human and system resources. Findings – Significant changes were observed in knowledge sourcing and sharing behaviors. Capture of the tacit knowledge of employees further resulted in reducing the impact of knowledge attrition. For instance, targeted communities of practice (CoPs) based on the presence of cliques within teams enabled teams to complete projects effectively and efficiently. Practical implications – The results are used to identify push and pull networks to enable effective knowledge management (KM). Results of this study reveal that analyzing knowledge flow patterns in a team and deploying a customized social computing platform that is tailored to address the needs of specific knowledge flow patterns within that team, significantly enhances collaborative sharing as opposed to a standardized “one-size-fits-all” platform. Originality/value – This paper is an original creation after research by the authors for a continuous assessment of KM within the organization.

scholarly journals Comparative Analysis of Knowledge Management Activities in SMEs: Empirical Study from a Developing Country

2018 ◽  
Vol 17 ◽  
pp. 523-530 ◽  
Author(s):  
Zorica Uzelac ◽  
Đorđe Ćelić ◽  
Viktorija Petrov ◽  
Zoran Drašković ◽  
Dalibor Berić
Keyword(s):  
Knowledge Management ◽  
Comparative Analysis ◽  
Empirical Study ◽  
Developing Country ◽  
Analysis Of Knowledge

Futures engineering in complex systems

foresight ◽  
2017 ◽  
Vol 19 (3) ◽  
pp. 306-322
Author(s):  
Hassan Bashiri ◽  
Amir Nazemi ◽  
Ali Mobinidehkordi
Keyword(s):  
Complex Systems ◽  
Conceptual Framework ◽  
Tacit Knowledge ◽  
Design Methodology ◽  
Futures Studies ◽  
Online Questionnaire ◽  
Content Type ◽  
Complex Theory ◽  
Cause And Effect ◽  
Iterative Processes

Purpose This paper attempts to apply complex theory in futures studies and addresses prediction challenges when the system is complex. The purpose of the research is to design a framework to engineer the futures in complex systems where components are divers and inter-related. Relations cannot be interpreted by cause and effect concept. Design/methodology/approach First, the authors shaped a conceptual framework based on engineering, complex theory and uncertainty. To extract tacit knowledge of experts, an online questionnaire was developed. To validate the proposed framework, a workshop method was adapted with NetLogo simulation. Findings Opinion of participants in the workshop which is collected through quantitative questionnaire shows that the framework helps us in understanding and shaping scenarios. Harnessing the complexity in developing the futures was the main objective of this paper with the proposed framework which has been realized based on the experience gained from the workshop. Originality/value Iterative processes are very important to harness the complexity in systems with uncertainty. The novelty of the research is a combination of engineering achievements in terms of computation, simulation and applying tools with futures studies methods.

Sign in / Sign up

Export Citation Format

Share Document