مقاله انگلیسی رایگان در مورد قابلیت آنالیز کلان داده در چابکی زنجیره تامین – امرالد ۲۰۱۸
مشخصات مقاله | |
انتشار | مقاله سال ۲۰۱۸ |
تعداد صفحات مقاله انگلیسی | ۲۲ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
منتشر شده در | نشریه امرالد |
نوع مقاله | ISI |
عنوان انگلیسی مقاله | Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility |
ترجمه عنوان مقاله | قابلیت آنالیز کلان داده در چابکی زنجیره تامین: اثر تعدیل کننده انعطاف پذیری سازمانی |
فرمت مقاله انگلیسی | |
رشته های مرتبط | مدیریت، مهندسی صنایع |
گرایش های مرتبط | مدیریت کسب و کار، لجستیک و زنجیره تامین |
مجله | تصمیم گیری در مدیریت – Management Decision |
دانشگاه | Montpellier Business School – Montpellier – France |
کلمات کلیدی | داده های بزرگ، نظریه احتمالی، بررسی قابلیت پویا، توانایی تحلیل، قابلیت تحلیل داده های بزرگ |
کلمات کلیدی انگلیسی | Big data, Contingency theory, Dynamic capability view, Analytics capability, Big data analytics capability |
کد محصول | E6443 |
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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۱٫ Introduction
The most successful organizations create supply chains that can respond to sudden and unexpected changes in the market (Lee, 2004). Supply chain management has gained popularity among organizations as a source of competitive advantage (Lee, 2002). Managing supply chains is extremely challenging task due to the current business outsourcing, globalization, short product life cycle, and continuous advancement in information technology (IT) (Lee, 2002; Christopher and Towill, 2002). Fisher (1997) attempted to match supply chain strategies (i.e. efficient vs responsive) to the product characteristics (i.e. functional vs innovative products). Lee (2002) extended Fisher’s work by proposing four strategies (i.e. efficient/ responsive/risk hedging/agile), to accommodate different degrees of demand and supply uncertainty. Hence, according to the situation, the organization’s supply chain agility (SCA) may directly affect its ability to produce and deliver innovative products to their customers at the right time, in the right place, in the right condition and at the right cost (Swafford et al., 2006; Khan and Pillania, 2008). Lee (2002) further argues that agile supply chains utilize strategies aimed at being responsive and flexible to customer’s needs, while the risks of supply shortages or disruptions are hedged by pooling inventory or other capacity resources. However, despite its immense popularity, SCA is still less understood (Braunscheidel and Suresh, 2009). The emerging literature has often used flexibility and agility interchangeably (Braunscheidel and Suresh, 2009). Liu et al. (2013) argues that amidst high environmental uncertainties, organizations are increasingly relying on IT capabilities to gain competitive advantage. Brusset (2016) further argues that supply chain managers are under extreme pressure to improve inventory turnover at minimal cost. Hence, in an effort to adapt the services and goods on offer to meet the customers’ changing tastes and behaviors, supply chain managers are under pressure to build agility in their supply chains to match the intense competition in markets (Gligor et al., 2016). However, an independent stream of research in recent years has led to the conceptualization of SCA as a distinct and different construct from flexibility (Christopher, 2000; Gligor and Holcomb, 2012a, b; Blome et al., 2013; Brusset, 2016; Dubey, Altay, Gunasekaran, Blome, Papadopoulos and Childe, 2018). The literature focusing on SCA and its impact on organizational performance is limited (Gligoret al., 2015) and has focused on the management practices needed to achieve the operational capabilities to enhance SCA from different managerial viewpoints, such as operations, strategy, information systems, marketing, and human resources (Brusset, 2016). |