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A Model for Analyzing the Barriers of Implementing Business Intelligence (BI) in the Tourism Industry of Iran, A Mixed Method Approach

Authors: AMENEH KHADIVAR; NEDA ABDOLVAND; LEILA NAZARI SALARI;

A Model for Analyzing the Barriers of Implementing Business Intelligence (BI) in the Tourism Industry of Iran, A Mixed Method Approach

Abstract

In this research, Barriers on BI implementation and utilization in Iran tourism industry have been performed using a mixed or combination methodology in both qualitative and quantitative measurement. In the qualitative part the grounded theory method and in qualitative section descriptive survey has been used. According to the results, the eleven obstacles based on its priority are as follow respectively: data barriers, managerial barriers, cultural barriers, lack of awareness and education, barriers related to human force, legal and political obstacles, lack of confidence and trust in knowledge transfer, organizational barriers, lack of systems integrity, obstacles related to funding of BI plans and barriers related to infrastructure. The results can facilitate utilizing and implementing of BI in Iran tourist industry.

Ameneh Khadivar is an Associate Professor at the Faculty of Social Sciences and Economics, University of Alzahra, Tehran, Iran. She has got a B.A in Industrial Engineering from Iran University of Science and Technology in Iran. She obtained her M.A in Information Technology Management from Tarbiat Modares University in Iran. She also received her Ph.D. in Systems Management from Tarbiat Modares University. Her research interests include Expert System, Business Intelligence, Knowledge Management, and Decision Support system, System Dynamic Information.

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Keywords

BUSINESS INTELLIGENCE, BARRIERS TO USING BUSINESS INTELLIGENCE, TOURISM INDUSTRY

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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