دانلود رایگان مقاله انگلیسی به کارگیری داده کاوی در استراتژی بازاریابی CRM: صنعت کافی شاپ در تایوان - امرالد 2017

عنوان فارسی
به کارگیری داده کاوی در استراتژی بازاریابی CRM: یک بررسی تجربی صنعت کافی شاپ در تایوان
عنوان انگلیسی
Applying data mining for online CRM marketing strategy: an empirical case of coffee shop industry in Taiwan
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
23
سال انتشار
2017
نشریه
امرالد - Emerald
فرمت مقاله انگلیسی
PDF
کد محصول
E7077
رشته های مرتبط با این مقاله
مهندسی صنایع، مدیریت، مهندسی کامپیوتر
گرایش های مرتبط با این مقاله
داده کاوی، بازاریابی، الگوریتم ها و محاسبات
مجله
مجله غذایی بریتانیا - British Food Journal
دانشگاه
Aletheia University - Taipai - Taiwan
کلمات کلیدی
رویکرد داده کاوی؛ کافی شاپ ها؛ الگوریتم خوشه بندی فازی؛ الگوریتم apriori؛ قوائد انجمن فازی، سیستم های بازاریابی CRM آنلاین
چکیده

Abstract


Purpose: The aim of this research is to propose a data mining approach for mining valuable markets for online customer relationship management (CRM) marketing strategy. The industry of coffee shop in Taiwan is employed as an empirical case study in this research. Design/methodology/approach: Via a proposed data mining approach, the study used fuzzy clustering algorithm and apriori algorithm to analyze customers for obtaining more marketing and purchasing knowledge of online CRM systems. Findings: The research found three hard markets and one fuzzy market. Furthermore, the study discovered two association rules and two fuzzy association rules. Originality/value: However, industry of coffee shops has been always a fast-growing and competitive business around the world. Thus, marketing strategy is important for this industry. The results and the proposed data mining approach of this research can be used in the industry of coffee shop or other retailers for their online CRM marketing systems. Keywords: data mining approach; coffee shops; fuzzy clustering algorithm; apriori algorithm; fuzzy association rules; online CRM marketing systems.

نتیجه گیری

5.1 Conclusions


The results of this research found three crisp markets and one fuzzy market, the study also mining two association rules and two fuzzy association rules for retailers. The size of the cluster A is 291(35%), the cluster B is 388(46%), the cluster C is 158(19%) and the fuzzy cluster F is 203(24.25%). However, the objective of this research is to propose a data mining approach for discovering customers marketing and purchasing rules, and also to integrate the fuzzy clustering and supervised-apriori-algorithm. Hence, the fuzzy association rules can be applied in e-business marketing systems to filter the valuable fuzzy target market and to understand shopping behaviors of the customers.


The scholar contribution of this study is to provide a data mining approach to integrate the fuzzy c-means and supervised apriori algorithm to generate the association rules in fuzzy mode. Via this case study, purchasing behaviors of the coffee shops’ customers in Taiwan have been shown. The industry of the coffee shops of Taiwan can easily apply their marketing projects on the most two market shares (cost and environmental considerations) for increasing royalties of customers to retain existed consumers, as well as attracting new consumers. Furthermore, for enhancing the Market C: Service Consideration, Pynnönen et al. (2014) suggested that businesses should offer full integrated service solutions for customers. Thus, the coffee shops in Taiwan can provide more free services for attracting more young customers, such as free Internet service in stores and free information and ordering services via smart phone apps.


بدون دیدگاه