مشخصات مقاله | |
انتشار | مقاله سال 2018 |
تعداد صفحات مقاله انگلیسی | 29 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 | |
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 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
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1. 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, 2013). 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). |