عنوان

A knowledge management based cloud computing adoption decision making framework

شماره

TLets690339

عنوان اصلي

A knowledge management based cloud computing adoption decision making framework

نام عام مواد

[Thesis]

نام نخستين پديدآور

Alhammadi, Abdullah

نام ناشر، پخش کننده و غيره

Staffordshire University

تاریخ نشرو بخش و غیره

2016

جزئيات پايان نامه و نوع درجه آن

Thesis (Ph.D.)

امتياز متن

2016

متن يادداشت

Cloud computing represents a paradigm shift in the way that IT services are delivered within enterprises. There are numerous challenges for enterprises planning to migrate to cloud computing environment as cloud computing impacts multiple different aspects of an organisation and cloud computing adoption issues vary between organisations. A literature review identified that a number of models and frameworks have been developed to support cloud adoption. However, existing models and frameworks have been devised for technologically developed environments and there has been very little examination to determine whether the factors that affect cloud adoption in technologically developing countries are different. The primary research carried out for this thesis included an investigation of the factors that influence cloud adoption in Saudi Arabia, which is regarded as a technologically developing country. This thesis presents an holistic Knowledge Management Based Cloud Adoption Decision Making Framework which has been developed to support decision makers at all stages of the cloud adoption decision making process. The theoretical underpinnings for the research come from Knowledge Management, including the literature on decision making, organisational learning and technology adoption and technology diffusion theories. The framework includes supporting models and tools, combining the Analytical Hierarchical Process and Case Based Reasoning to support decision making at Strategic and Tactical levels and the Pugh Decision Matrix at the Operational level. The Framework was developed based on secondary and primary research and was validated with expert users. The Framework is customisable, allowing decision makers to set their own weightings and add or remove decision making criteria. The results of validation show that the framework enhances Cloud Adoption decision making and provides support for decision makers at all levels of the decision making process.

مستند نام اشخاص تاييد نشده

Alhammadi, Abdullah

مستند نام تنالگان تاييد نشده

Staffordshire University

نام الکترونيکي

فرمت انتشار

p

نوع ماده

[Thesis]

کد کاربرگه

276903

سطح دسترسي

a

تكميل شده

Y