Indian Journal of Science and Technology
DOI: 10.17485/ijst/2015/v8i35/68800
Year: 2015, Volume: 8, Issue: 35, Pages: 1-8
Original Article
Alireza Shahraki 1 , Arsalan Dezhkam2* and Rahil Dejkam1
1 Department of Industrial Engineering, University of Sistan and Baluchestan, Iran; [email protected], [email protected]
2 Department of Basic Sciences, Faculty of Marine Sciences, Chabahar Maritime University, Iran; [email protected]
Background/Objectives: The aim of this research work is to demonstrate that the business intelligence based tools are capable to enhance the CRM successful implementation. Methods/Statistical Analysis: To gather preliminary data the authors used questionnaire. The first questionnaire evaluates variables influencing the successful implementation of CRM using business intelligence. The second questionnaire also examines various aspects of customer orientation as the output deals with the use of Customer Relationship Management. To test the conceptual model and hypotheses, the PLS technique is deployed. It is a component-based estimation approach that differs from the covariance-based structural equation modeling. Findings: Hypothesis test showed that the test statistics in all three main hypotheses and other underlying assumptions is greater than the critical value of t at the level of 5% (1/96), i.e., the observed correlation between model relationship is significant. As a result, all three information technology, knowledge management and organizationalfieldsbasedonbusiness intelligence,have adirect andpositive impactonsuccessfulCustomerRelationship Management implementation. For the future works it’s recommended to develop the presented conceptual model of this work in a more complex organization in terms of uncertaintiy and using fuzzy data. Application/Improvement: According to the results, data integration to CRM success is of special importance, therefore managers should deploy required standards for integrating existing data and processes in the organization.
Keywords: Business Intelligence, CRM, Customer Orientation, Knowledge Management, Partial Least Squares
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