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Organizational implications of a comprehensive approach for cloud-storage sourcing

机译:全面方法对云存储采购的组织影响

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Cloud-computing facilitates consumers to source online storage-services on a pay-as-you-go basis. The sourcing of storage-as-a-service (STaaS) requires a decision maker to contend with several elements such as pricing structure, application characteristics and quality-of-service requirements, in addition to tactical considerations such as risk propensity and supplier diversification. This makes STaaS sourcing a complex task. Discussion on STaaS sourcing models addressing these aspects and their utility to decision-makers is, however, scant. In this paper, we propose a two-stage holistic approach based on Data Envelopment Analysis (DEA) and Goal programming (GP). We derive insights provided by these models from 10800 runs using market-based data. We also use an experiment to assess our hypothesis concerning the impact of task complexity on decision-quality. Both these experiments have implications for different business scenarios in the STaaS market, and for decision-making. We discuss these managerial implications, and present a prototype Decision Support System (DSS) to aid STaaS selection.
机译:云计算可帮助消费者按需付费,以获取在线存储服务。存储即服务(STaaS)的采购要求决策者应对诸如价格结构,应用程序特征和服务质量要求之类的若干要素,以及诸如风险倾向和供应商多元化等战术考虑。这使STaaS采购成为一项复杂的任务。但是,关于针对这些方面及其对决策者的实用性的STaaS采购模型的讨论很少。在本文中,我们提出了一种基于数据包络分析(DEA)和目标编程(GP)的两阶段整体方法。我们使用基于市场的数据从10800次运行中得出这些模型提供的见解。我们还使用实验来评估关于任务复杂性对决策质量的影响的假设。这两个实验都对STaaS市场中的不同业务场景以及决策产生了影响。我们讨论了这些管理意义,并提出了原型决策支持系统(DSS)以帮助选择STaaS。

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