مطالعات مدیریت کسب و کار هوشمند

نویسندگان

1 عضو هیئت علمی، گروه مدیریت کسب‌وکار، دانشکده مدیریت، دانشگاه خوارزمی، تهران.

2 کارشناس ارشد، مدیریت فناوری اطلاعات، دانشکده مدیریت، دانشگاه الزهراء واحد ارومیه (نویسنده مسئول)؛ zahraa.beyrami@gmail.com

چکیده

 
با گسترش اینترنت، سازمان‌ها از روش‌های مختلف E-CRM استفاده می‌کنند. یکی از اهداف سازمان‌ها در استفاده از E-CRM افزایش وفاداری مشتریان و حفظ مشتریان وفادار جهت دستیابی به مزیت رقابتی و سودآوری است. هدف این پژوهش بررسی تأثیر E-CRM بر وفاداری مشتریان بانک ملت با استفاده از تکنیک‌های داده‌کاوی است. در این پژوهش از روش‌های خوشه‌بندی با الگوریتم K-means و شبکه‌های عصبی (با الگوریتم پس انتشار خطا) و مدل LRFM از طریق برنامه‌نویسی در نرم‌افزارهای متلب و اکسل استفاده شده است. نتایج پژوهش نشان داد که با افزایش میزان استفاده مشتریان از خدمات E-CRMوفاداری آن‌ها افزایش می‌یابد. رابطه بین E-CRM، مؤلفه‌های مدل LRFM و وفاداری یک رابطه غیر‌خطی است و میزان تغییر در وفاداری به ازای تغییر E-CRM، مقداری ثابت نیست. میزان افزایش وفاداری تابعی از مؤلفه‌های LRFM، مقدار E-CRM و اوزان به‌دست‌آمده در شبکه عصبی است.
 

کلیدواژه‌ها

عنوان مقاله [English]

The Impact of E-CRM on Customer Loyalty Using Data Mining Techniques

نویسندگان [English]

  • Hassan Rangriz 1
  • Zahra Bayrami Shahrivar 2

1 Faculty Member, Faculty of Management, Department of MBA, Kharazmi University, Tehran

2 MA, Information Technology Management, Alzahra University, Urmia Branch (Corresponding Author: zahraa.beyrami@gmail.com)

چکیده [English]

With the expansion of the Internet, various tools have been used to communicate with customers in organizations, and organizations use different E-CRM methods to create competitive advantages. Since customer loyalty is critical to achieving competitive advantage and profitability for organizations, one of the goals of organizations in using E-CRM is to maintain and increase customer loyalty. Therefore, considering the importance of the impact of various E-CRM services on customers’ loyalty, the purpose of this study is to investigate the impact of E-CRM on the loyalty of Bank Mellat customers using data mining techniques. The data required for this research were extracted from Bank Mellat databases. Data mining techniques include clustering with K-means algorithm and neural networks (using error-relay algorithm) and LRFM model through programming in MATLAB and Excel software were used to analyze the data. The results showed that with increasing use of E-CRM services, customers’ loyalty increases. The relationship between E-CRM, the components of LRFM model, and loyalty is a nonlinear and the change in loyalty as E-CRM changes is not a constant.  The increase in loyalty is a function of LRFM components, the amount of E-CRM and weights obtained in the neural network.  

کلیدواژه‌ها [English]

  • E-CRM
  • Customer Loyalty
  • Data Mining
  • LRFM
 
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