Library and Information Science Research, Volume (42), No (2), Year (2020-4) , Pages (101004-101015)

Title : ( The competitive intelligence diamond model with the approach to standing on the shoulders of giants )

Authors: narges oraee , Azam Sanatjoo , Mohamad Reza Ahanchian ,

Citation: BibTeX | EndNote

Abstract

Organizations that implement a competitive intelligence process are more successful in a competitive environment. To do so correctly there is a need for a comprehensive model that, in addition to eliminating the defects of the previous models, describes the phases and indicators and also illustrates the relationship between them. This research meets such a need and presents a developed model. The ongoing research is based on a mixed approach. The meta-synthesis method was used to identify the initial model in the first stage and the delphi method was used to validate and modify the initial model, as well as to understand the relationship between all the phases of this process in the second stage. Two samples were used, the first included all the papers in the competitive intelligence field, of which 45 were selected. The second sample included experts in intelligence. Organizations can use this comprehensive model for deployment, correct implementation, and the practice of competitive intelligence.

Keywords

, Competitive Intelligence, Universities
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@article{paperid:1079789,
author = {Oraee, Narges and Sanatjoo, Azam and Ahanchian, Mohamad Reza},
title = {The competitive intelligence diamond model with the approach to standing on the shoulders of giants},
journal = {Library and Information Science Research},
year = {2020},
volume = {42},
number = {2},
month = {April},
issn = {0740-8188},
pages = {101004--101015},
numpages = {11},
keywords = {Competitive Intelligence; Universities},
}

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%0 Journal Article
%T The competitive intelligence diamond model with the approach to standing on the shoulders of giants
%A Oraee, Narges
%A Sanatjoo, Azam
%A Ahanchian, Mohamad Reza
%J Library and Information Science Research
%@ 0740-8188
%D 2020

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