مقاله انگلیسی رایگان در مورد مدیریت ارتباط با مشتری فعال شده با کلان داده – الزویر ۲۰۱۸

elsevier

 

مشخصات مقاله
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۲۹ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه الزویر
نوع مقاله ISI
عنوان انگلیسی مقاله Big Data-enabled Customer Relationship Management: A holistic approach
ترجمه عنوان مقاله مدیریت ارتباط با مشتری فعال شده با کلان داده
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مدیریت
گرایش های مرتبط مدیریت منابع انسانی، مدیریت دانش
مجله پردازش اطلاعات و مدیریت – Information Processing and Management
دانشگاه Department of Energy – University of Pisa – Pisa – Italy
کلمات کلیدی کلان داده، CRM، بررسی ادبیات، عوامل موفقیت بحرانی (CSFs)
کلمات کلیدی انگلیسی Big Data, CRM, Literature review, Critical Success Factors (CSFs), Word tree
کد محصول E6198
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بخشی از متن مقاله:
۱٫ Introduction

Big Data (BD) is considered as a potential enabling factor of business process innovation (Fosso Wamba, Akter, Edwards, Chopin, & Gnanzou, 2015; Loebbecke & Picot, 2015) and as a possible new form of value creation, although the mechanisms of such creation are still unclear (George, Haas, & Pentland, 2014). In fact, these innovations are potentially triggered by the current increased data availability in terms of volumes, variety, and velocity, which are data characteristics typically associated with the concept of BD. BD and BD analytics are transforming customer-facing industries (Fosso Wamba, Akter, & Bonicoli, 2013), which are increasingly collecting large amounts of customer data, like customers’ shopping behaviour, for enabling a real-time decision making (Barton & Court, 2012; Bean & Kiron, 2013; Davenport, Barth, & Bean, 2012). Companies are coping with customer data spread among an increasing number of data sources, often external or not structured. They are figuring out the potential value of data for generating insights on customers, but they are still struggling to integrate the information stemming from the innovative data sources into the Customer Relationship Management (CRM) decisions (Phillips-Wren & Hoskisson, 2015). Despite this difficulty, some, albeit few, firms have already been able to overcome such a hindrance concretely for CRM purposes: for instance, Sears Holding has been employing BD, gathered from several data warehouses related to its brands, for offering more timely, sharp, and granular personalized promotions (McAfee & Brynjolfsson, 2012); Caesars Entertainment utilizes data from its Total Reward loyalty program, realtime play, and web clickstreams for targeting customers with real-time offers through mobile devices, for improving customer understanding, and for reducing the waiting time for playing for both regular and occasional customers (Davenport & Dyché, ۲۰۱۳). One of the most recent challenges for CRM is to attempt to harness new heterogeneous data sources for developing innovative value propositions, for instance by drawing customer data from social networks (Acker, Gröne, Akkad, Pötscher, & Yazbek, 2011; Diffley & McCole, 2015; Faasse, Helms, & Spruit, 2011; Greenberg, 2010; Sigala, 2011; Trainor, Andzulis, Rapp, & Agnihotri, 2014).

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