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Application of Fuzzy Logic for Advertising Marketing Campaigns | ||
| Control and Optimization in Applied Mathematics | ||
| دوره 5، شماره 2، مهر 2020، صفحه 25-37 اصل مقاله (584.92 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.30473/coam.2021.58392.1160 | ||
| نویسندگان | ||
| Abbas Bashiri؛ Seyed Mehdi Mirhosseini-Alizamini* ؛ Mohammad Mehdi Nasrabadi | ||
| Department of Mathematics, Payame Noor University (PNU), P.O. Box. 19395-4697, Tehran, Iran. | ||
| چکیده | ||
| Evaluation of advertising marketing campaigns is a very important and complex task, so far no comprehensive model has been presented in this regard. The present study aims to provide a decision framework for evaluating marketing campaigns. This article collects real-world data from an Iranian bank deposit marketing campaign. For this purpose, 250 cases were considered to extract the rules and 60 cases were considered as test data. Information is provided on 15 important parameters of marketing education, defaults, age, occupation, marriage, day, contact, balance, housing, loans, previous contact, previous outcome, month, call duration, and campaigns. A fuzzy expert system was designed with 12 rules after reviewing the rules and removing similar and contradictory rules by using their degree calculation. In this system, by integrating some factors, finally, 6 input variables and one output variable were considered that were used by the product inference engine, singleton fuzzifier, and center average defuzzifier. It was observed that the designed fuzzy expert system provides very good results. | ||
| کلیدواژهها | ||
| Fuzzifier؛ Defuzzifier؛ Fuzzy expert؛ Input-output | ||
| عنوان مقاله [English] | ||
| کاربردی از منطق فازی بر بازاریابی کمپینهای تبلیغاتی | ||
| نویسندگان [English] | ||
| عباس بشیری؛ سید مهدی میرحسینی عالیزمینی؛ محمد مهدی نصر آبادی | ||
| ایران، تهران، گروه ریاضی، دانشگاه پیام نور، صندوق پستی 4697-19395 | ||
| چکیده [English] | ||
| با توجه به اینکه ارزیابی کمپینهای بازاریابی تبلیغاتی یک کار بسیار مهم و پیچیده است، ولی تاکنون مدل جامعی در این زمینه ارائه نشده است. مطالعه حاضر با هدف ارائه یک چارچوب تصمیم برای ارزیابی فعالیتهای بازاریابی بر منطق فازی پایهریزی شده است که جمعآوری دادههای واقعی پژوهش از یک کمپین بازاریابی سپرده بانکی ایران صورت گرفته است. برای این منظور تعداد 250 مورد جهت استخراج قوانین و 60 مورد به عنوان دادههای تست در نظر گرفته شدند. اطلاعات 15 پارامتر بازاریابی تبلیغاتی اعم از تحصیلات، پیش فرض، سن، شغل، ازدواج، روز، تماس، مانده، مسکن، وام، تماس قبلی، نتیجه کمپین بازاریابی قبلی، ماه، مدت زمان تماس و کمپین دریافت گردید. سیستم خبره فازی پس از بررسی قوانین و حذف قوانین مشابه و متناقض با بهرهگیری از محاسبه درجه آنها، با 12 قانون طراحی گردید. در این سیستم با ادغام برخی عوامل در نهایت 6 متغیر ورودی و یک متغیر خروجی در نظر گرفته شد که با موتور استنتاج حاصلضرب، فازیساز منفرد و غیرفازیساز میانگین مراکز مورد استفاده قرار گرفت. مشاهده میشود که سیستم طراحی شده نتایج بسیار خوبی را ارائه میدهد. | ||
| کلیدواژهها [English] | ||
| فازیساز, غیرفازیساز, خبره فازی, ورودی-خروجی | ||
| مراجع | ||
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[1] Abdoli M., Sheykhesmaeli S. 2015. “Identification of factors influencing the evaluation of marketing channels”, Second National Conference on Marketing Research, Tehran. (in Persian).
[2] Achrol R. S., Etzel M. J. 2003. “The structure of reseller goals and performance in marketing channels”, Journal of the Academy of Marketing Science, 31 (2), 146-163.
[3] Agatz N. A., Fleischmann M., van Nunen J. A. 2008. “E-fulfillment and multi-channel distribution-A review”, European Journal of Operational Research, 187 (2), 339-356.
[4] Alptekinoglu A., Tang C. S. 2005. “A model for analyzing multi-channel distribution systems”, European Journal of Operational Research, 163 (3), 802-824.
[5] Bond D. 2017.“Advertising agencies squeezed by tech giants”, The Financial Times, Available https://www.ft.com/content/9a9ac60a-575a-11e7-9fed-c19e2700005f.
[6] Chen G. Q., Wei Q. 2002. “Fuzzy association rules and the extended mining algorithms”, Information Sciences, 147, 201-228.
[7] Chiv R., Nie F., Wu S., Tum S. 2020. “Analysis of Factors Influencing Marketing Channel Choices by Smallholder Farmers: A Case Study of Paddy Product in Wet and Dry Season of Prey Veng Province, Cambodia”, Journal of Sustainable Development, 147, 201-228.
[8] Dashore P., Kumar-Jain S. 2009. “Fuzzy Rule Based System and Metagraph for Risk Management in Electronic Banking Activities”, International Journal of Engineering and Technology, 1 (1), 1793-8236.
[9] Dehghandar M., Khaloozadeh H., Soltanian F., Keshavarz M. 2016. “Application of Fuzzy Logic to determine the retentive causes of pulse body the pulse parameters”, Iranian Traditional Medicine, Journal of Multidisciplinary Engineering Science and Technology, 3 (2), 3881-3884.
[10] Dehghandar M., Pabasteh M., Heydari R. 2021. “Diagnosis of COVID-19 disease by fuzzy expert system designed based on input-output”, Journal of Control, 14 (5), 71-78. (in Persian).
[11] Deshmukh A., Lakshminarayana T. 1998. “A rule-based fuzzy reasoning system for assessing the risk of management fraud”, International Journal of Intelligent Systems in Accounting, Finance & Management, 4, 231-41.
[12] Ebrahimnejad A., Jafarnejad Ghomi S., Mirhosseini-Alizamini S. M. 2018. “A revisit of numerical approach for solving linear fractional programming problem in a fuzzy environment”, Applied Mathematical Modelling, 57, 459-473.
[13] Ebrahimnejad A., Jafarnejad Ghomi S., Mirhosseini-Alizamini S. M. 2017. “A new approach for solving fully fuzzy linear fractional programming problems”, 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI-2017), 1-4.
[14] Ghen G. Q. 1998. “Fuzzy Logic in Data Modelling: Semantics, Constraints and Database Design”, Kluwer Academic Publishers, Boston.
[15] Guo S., Zhao H. 2017. “Fuzzy best-worst multi-criteria decision-making method and its applications”, Knowledge-Based systems, 121, 23-31. [16] Jarvinen J., Karjaluoto H. 2015. “The use of Web analytics for digital marketing performance measurement”, Industrial Marketing Management, 50, 117-127.
[17] Kamarzarrin M., Eghbal N. 2021. “Modeling of self-assessment system of COVID-19 disease diagnosis using Type-2 Sugeno fuzzy inference system”, Journal of Control, 14 (5), 49-57. (in Persian)
[18] khan N., Khan F. 2013. “Fuzzy Based Decision Making for Promotional Marketing Campaigns”, International Journal of Fuzzy Logic Systems (IJFLS), 3 (1), 65-77.
[19] Kyaw N. N., Ahn S., Lee S. H. 2018. “Analysis of the Factors Influencing Market Participation among Smallholder Rice Farmers in Magway Region, Central Dry Zone of Myanmar”, Sustainability, 10, 4441. https://doi.org/10.3390/su10124441
[20] Lewis R. A., Reiley D. H. 2013. “Down-to-the-minute effects of super bowl advertising on online search behavior”, Proceedings of the 14th ACM Conference on Electronic Commerce, Philadelphia, PA, Array, 639-656. https://doi.org/10.1145/2492002.2482600.
[21] Meng F., Chen X. 2019. “A robust additive consistency-based method for decision making with triangular fuzzy reciprocal preference relations”, Fuzzy Optimization and Decision Making, 17 (1), 49-73. [22] Nasrollahi M., Fathi M. R., Faghih A. 2018.“Designing a Model for Evaluating Marketing Channels based on the Fuzzy Best-Worst and Fuzzy EDAS Methods”, Journal of Business Management, 10 (3), 695-712. (in Persian) [23] Saura J. R., Palos-Sanchez P., Cerda Suarez L. M. 2017. | ||
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