خرده ‌فروشی در عصر آنالیز کلان داده ها
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خرده ‌فروشی در عصر آنالیز کلان داده ها

عنوان فارسی مقاله: خرده ‌فروشی و تحقیقات خرده ‌فروشی در عصر آنالیز کلان داده ها
عنوان انگلیسی مقاله: Retailing and retailing research in the age of big data analytics
مجله/کنفرانس: مجله بین المللی تحقیقات بازاریابی – International Journal of Research in Marketing
رشته های تحصیلی مرتبط: مدیریت
گرایش های تحصیلی مرتبط: بازاریابی
کلمات کلیدی فارسی: خرده‌ فروشی، آنالیز کلان داده ها
کلمات کلیدی انگلیسی: Retailing، Big data analytics
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.ijresmar.2019.09.001
دانشگاه: Department of Marketing, School of Economics and Management, Tilburg University, Warandelaan 2, 5000LE Tilburg, The Netherlands
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 4.017 در سال 2019
شاخص H_index: 89 در سال 2020
شاخص SJR: 3.790 در سال 2019
شناسه ISSN: 0167-8116
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 12
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E15009
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


۱٫ Introduction


۲٫ Retailing: an attractive research domain


۳٫ Retailing and big data


۴٫ Big data: opportunities and challenges to retail managers


۵٫ Big data in retailing: opportunities and challenges for retail researchers


۶٫ Big data in retailing: implications for other stakeholders


۷٫ Conclusion


References

نمونه متن انگلیسی مقاله

Abstract


As a research domain, the retail sector has always had many appealing features, such as its size, its multi-faceted and dynamic nature, the possibility for researchers to exploit their own domain knowledge, and an extensive coverage by business analysts. In addition, the above-average availability of good-quality data has historically been an additional selling point to empirical researchers. The paper considers to what extent the latter still holds, and explores a number of additional opportunities and challenges that emerge from the ongoing big data revolution. This is done from five perspectives: retail managers, retailing researchers, publicpolicy makers, investors, and retailing educators.


Introduction


The papers that have appeared in IJRM’s invited “EMAC Distinguished Scholar” series have covered a wide range of topics. A common theme in most of these contributions is that the authors have taken the opportunity to reflect not only on the past, but also (and even more so) on the future of the field. In so doing, they have focused either on the marketing discipline as a whole (see, e.g., the contributions in the current issue by Don Lehmann (2019) and Roland Rust (2019)) or on the sub-field they are most closely associated with (see, e.g., Wierenga (2011) on managerial decision making, or Lilien (2016) on the B2B knowledge gap). In terms of my own scientific career, my first professional publication was on the survival rate of retail stores (Dekimpe & Morrison, 1991), and throughout the subsequent years/decades, most of my work has continued to focus on retailing-related issues. In this article, I will first reflect on why I feel the retailing sector is a fascinating and fertile ground for managerially relevant academic research. I will argue how the above-average availability of good-quality data has historically been a key selling point for empirical researchers. After that, I will consider to what extent this still holds, and explore a number of additional opportunities and challenges that emerge from the ongoing, and rapidly accelerating, big data revolution. I will do so from five perspectives: retail managers, retailing researchers, as well as public-policy makers, investors, and retailing educators. The retailing sector is an ideal setting for such a discussion, as analysts like to present the sector as a poster child for all the benefits that one can envision from the use of big data. Industry reports have proclaimed that retailing is “one of the hottest markets for big data analytics” (Ingram Micro, 2018), that “big data is especially promising and differentiating for retailers” (IBM Analytics, 2018), or that big data will be “a complete game changer in the retail sector” (Forbes, 2015). A 2011 McKinsey report put forward that big data have the potential to increase retailers’ operating margins with up to 60%, and cause a sector-wide annual productivity gain of up to 1% in the next five years (McKinsey, 2011). Similar enthusiastic endorsements have appeared in the academic literature. Grewal, Roggeveen, and Nordfält (2017), for example, argue how new technologies along with big data/predictive analytics will cause a quantum leap in retailers’ understanding of the shopping process.

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