Statistics of evaluation indicators of observation models and their scoring

Document Type : Research Paper

Authors

1 PhD candidate of Futures Studies of Hazrat Waliasr Research Institute, Imam Hossein University

2 Assistant Professor of Futures Studies, Imam Hossein University

3 Assistant Professor of Futures Studies. Imam Hossein University

Abstract

Purpose: Observation is one of the important pillars of futures studies and the introduction of projects and researches. If it likened to a building, correct observation will be like a solid and reliable foundation for it. Different researchers have presented several observation models. These models are presented based on the surrounding conditions and characteristics of each research and are different from each other.The main purpose of the current research is to calculate the evaluation indicators of observation models and to identify the characteristics, strengths and weaknesses of 36 existing models, focusing on last ten years and common models in the past based on the aforementioned indicators, and, other goals Like determining the scoring relationship, observation models were also followed.
Method: This research is practical from the point of view of the goal and is considered as mixed research and it uses the methods of library studies, expert panel and questionnaire.
Findings: In this research, 36 models were extracted and explained from among the existing observation models, and twelve final indicators were determined based on the opinion of experts in order to evaluate them. The mentioned indicators were weighted based on their importance by experts and a relationship was presented to score the observation models and finally 36 observation models were scored based on it.
Conclusion: The results show that the three observation models of Momenizahed, Sakalidis and Cuhls got the most points. Based on the final evaluation indicators, observation models were introduced that had more strengths in each of them.

Keywords

References

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Journal of Iran Futures Studies
Volume 9, Issue 1 - Serial Number 12
September 2024
Pages 1-31

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