نوع مقاله : مقالات پژوهشی به زبان انگلیسی
نویسندگان
گروه اقتصاد کشاورزی، دانشکده کشاورزی، دانشگاه فردوسی مشهد، مشهد، ایران
چکیده
بازارهای خردهفروشی شهری، بازارهای خردهفروشی دولتی هستند که اخیراً در ایران با هدف افزایش رفاه مصرفکنندگان و تولیدکنندگان تأسیس شدهاند. برای دستیابی به این هدف و گسترش حضور در بخش خردهفروشی شهری، درک جامعی از رفتار مصرفکننده در این بازارها ضروری است. این مطالعه با استفاده از الگوریتم C4.5 به بررسی عوامل مختلف اجتماعی-اقتصادی مؤثر بر تصمیمگیری مصرفکنندگان در بازارهای خردهفروشی پرداخته است. دادهها از طریق نظرسنجی از 189 مصرفکننده با استفاده از روش نمونهگیری تصادفی در شهر مشهد در سالهای 1398 و 1399 جمعآوری شد. نتایج نشان داد که آگاهی از تخفیفهای موجود بهطور قابل توجهی انتخاب مصرفکننده را در بازارهای خردهفروشی شهری تحت تأثیر قرار میدهد. با این حال، علیرغم تخفیفهای موجود، آگاهی در میان مصرفکنندگان پایین است که نیاز به بازنگری در استراتژیهای تبلیغاتی میباشد. همچنین نتایج نشان داد تجربه خرید از بازارهای شهری، درآمد خانوار و تحصیلات از جمله عوامل تأثیرگذار بر انتخاب مصرفکننده میباشند. یافتههای این مطالعه میتواند بینشهای ارزشمندی برای سیاستگذاران و سهامداران فراهم آورد که در پی افزایش اثربخشی بازارهای خردهفروشی محلی در ایران هستند. علاوه بر این، با بهرهگیری از این بینشها در زمینه رفتار مصرفکننده و پویایی بازار، این بازارها میتوانند رونق گرفته و نقش بسزایی در بهبود بخش خردهفروشی و اقتصاد ایران ایفا کنند. در این راستا، توصیههایی مانند کمپینهای تبلیغاتی، استراتژیهای آموزشمحور، همکاری با تولیدکنندگان محلی و سیاستهای بازاریابی فراگیر با هدف بهبود دسترسی همه مصرفکنندگان به بازارهای خردهفروشی شهری ارائه گردید.
کلیدواژهها
موضوعات
عنوان مقاله [English]
A Data Mining Approach to Consumers’ Choice of Retail Market: The Case of Urban Retail Markets in Iran
نویسندگان [English]
- H. Hashemzadeh
- N. Yousefian
- S. Esfandiari Bahraseman
- A. Karbasi
- A. Firoozzare
Department of Agricultural Economics, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran
چکیده [English]
Urban retail markets are state-owned retail markets that were recently established in Iran to increase the welfare of consumers and producers. To achieve this goal and expand its presence in the Iranian retail sector, it is essential to gain a comprehensive understanding of consumer behavior within these markets. This study examines the various socio-economic factors influencing consumers' decisions in the retail market by using the C4.5 algorithm. The data were collected using a random sampling method through a survey of 189 consumers, focusing on the population of Mashhad, Iran, during 2019-2020. Results revealed that awareness of available discounts significantly drives consumer choices in urban retail markets. Despite existing discounts, awareness among consumers remains low, suggesting a need to review promotional strategies within the marketing mix. The study also identifies previous purchases from urban markets, household income, and education as influential factors. Findings offer valuable insights for policymakers, market strategists, and stakeholders seeking to enhance the effectiveness of local retail markets in Iran. By leveraging insights into consumer behavior and market dynamics, these markets can thrive, benefiting Iran's retail sector and overall economy. Following the study, recommendations such as enhanced promotional campaigns, education-oriented strategies, loyalty programs, collaborations with local producers, and inclusive marketing policies was made aim to improve access for all consumers to urban retail markets.
کلیدواژهها [English]
- Consumer behavior
- Data mining
- Decision tree
- Machine learning
©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
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