Developing a marketing decision model using a knowledge-based system |
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| Affiliation: | 1. Communication Faculty, Ataturk University, 25240 Erzurum, Turkey;2. Department of Electronics and Telecommunications Engineering, Ataturk University, 25240 Erzurum, Turkey;3. Vocational College of Erzurum, Ataturk University, 25240 Erzurum, Turkey;4. Faculty of Economics and Administrations, Ataturk University, 25240 Erzurum, Turkey;5. Vocational College of Kirsehir, Gazi University, Kirsehir, Turkey;1. North Carolina Burn Disaster Program, EMS Performance Improvement Center, University of North Carolina School of Medicine, United States;2. WFBMC Burn Center, Wake Forest Baptist Health System, Wake Forest University School of Medicine, United States;3. Healthcare System and Hospital Preparedness Program Coordinator, North Carolina Office of EMS, United States;4. Department of Emergency Medicine, University of North Carolina School of Medicine, United States;5. ESF8 Program Manager, Bureau of Preparedness and Response, Emergency Preparedness and Community Support/Florida Department of Health, United States;6. Burn Center, Orlando Regional Medical Center, University of Central Florida College of Medicine, United States;7. North Carolina Jaycee Burn Center, University of North Carolina School of Medicine, United States;1. The Hebrew University, Jerusalem 91905, Israel;2. IDC, Herzliya, Israel;1. Hofstra Northwell School of Medicine, Manhasset, NY;2. Cardiac Clinic of Kissimmee, Fla;3. New York University School of Medicine;1. Department of Internal Medicine I, University Medical Center Regensburg, Germany;2. Center of Clinical Studies, University Medical Center Regensburg, Germany;3. Department of Cardiothoracic Surgery, University Medical Center Regensburg, Germany;2. Department of Cardiac Surgery, Sheba Medical Center, Tel Hashomer, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel;1. Pediatric Department, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia |
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| Abstract: | This paper describes using a knowledge-based system for developing a marketing decision model. The approach used in this study uses a decision table as a knowledge engineering tool. The decision table is used as a means of representing a set of decision rules to construct a developed marketing decision model. To support the modeling process, Prologa, an existing decision table engineering workbench, is used. The developed marketing decision model is used to determine the entrance time of a new product into market by utilizing knowledge-based systems. Presentation of a new product to the market at the best time will provide an advantage to competing companies and will increase their market share. |
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