Digital Transformation: Evaluating Emerging Technologies. Группа авторов
Читать онлайн книгу.17.F. Lambert, “Volvo unveils new all-electric garbage truck with up to 200 km of range”, Electric.co.uk, 9 May 2018. https://electrek.co/2018/05/09/volvo-all-electric-garbage-truck/.
18.W. Pentland, “Nissan pilots vehicle-to-grid technology In Denmark”, Forbes, 8 December 2015. https://www.forbes.com/sites/williampentland/2015/12/08/nissan-pilots-vehicle-to-grid-technology-in-denmark/.
19.Nissan Motor Corporation Global Newsroom, “Enel Energia, Nissan Italia and IIT join forces for the development of electric mobility in Italy”, Press Release, 5 February 2017. https://newsroom.nissan-global.com/releases/enel-energia-nissan-italia-andiit-join-forces-for-the-development-of-electric-mobility-in-italy.
20.M. Kane, “Nissan LEAF Is Germany’s First V2G-Approved Electric Car”, Inside EVs, 23 October 2018. https://insideevs.com/nissan-leaf-germanys-first-v2g-electric-car/.
21.T. Casey, “US military will get thousands more EVs as SPIDERS web grows”, Clean Technica, 2 November 2013. https://cleantechnica.com/2013/11/02/us-military-electric-vehicles/.
22.D. Unger, (2013, October 31). “US military warms to electric cars”, The Christian Science Monitor, 31 October 2013. https://www.csmonitor.com/Environment/Energy-Voices/2013/1031/US-military-warms-to-electric-cars.
23.Naval Facilities Engineering Command, “Technology transition final public report: Smart Power Infrastructure Demonstration for Energy Reliability and Security (SPIDERS)”, Report, Washington, DC, 31 December 2015. https://www.energy.gov/sites/prod/files/2016/03/f30/spiders_final_report.pdf.
24.D. F. Kocaoglu and T. U. Daim, Hierarchical Decision Modeling: Essays in Honor of Dundar F. Kocaoglu (Cham, Switzerland: Springer, 2015).
25.N. J. Sheikh, K. Kim and D. F. Kocaoglu, “Use of hierarchical decision modeling to select target markets for a new personal healthcare device”, Health Policy and Technology 5, 2 (2016) 99–112. doi:10.1016/j.hlpt.2015.12.001.
26.M. Abbas, “Consistency analysis for judgment quantification in Hierarchical Decision Model”, Dissertation, Portland State University, 2016.
Chapter 2
Technical Transformation: Cloud Services
Cody Miller*, Wendy Lally*, Liyan Xiao*, David Burchfield*, Shihab Hanayneh* and Tugrul Daim*,†,‡
*Portland State University, Portland, Oregon, USA
† Higher School of Economics, Moscow, Russia
‡ Chaoyang University of Technology, Taiwan
Abstract
Cloud migration is a complex process, and many decisions must be made before the process can be completed. This paper identifies the key criteria of cloud migration and offers a model for determining one of the decisions: which cloud service strategy (Infrastructure as a Service (IaaS), Platform as a Service (PaaS), or Software as a Service (SaaS)) to use for any particular cloud migration project? This paper describes some of these types of services as well as presents a Hierarchical Decision Model (HDM) structure for choosing a service strategy.
The authors have created the HDM model, which may be used as a basis for cloud service strategy decision-making at a wide variety of companies. This implementation of the model has been designed for a fictional company, Best Men’s Fashion (BMF) LLC, and the pairwise comparison judgments are based solely upon the priorities of that company.
Keywords: Technology assessment, infrastructure as a service, platform as a service, software as a service.
1.Introduction
The cloud service strategy Hierarchical Decision Model (HDM) model was developed using four levels of criteria. The first level—Mission Level—was crafted to “determine the model of cloud service strategy for the company”. In the second level called the Objective Level, criteria were gathered from a literature review and the opinions of experts. The four objectives in this level are Technical, Security, Economic and Management. To limit the scope of this project as well as to keep the expert pairwise comparison data points manageable, the team focused on two criteria per objective in the third level. So, the criteria of the Security objective are Protection and Migration: Compliance, Scalability and Migration: Technical Complexity for the Technical objective, Service Charges and Migration: Costs for the Economic objective, and Support Capabilities and Migration: Business Complexity for the Management objective. The last level contains three cloud service strategies—Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS)—for the HDM to compare.
This model evaluation had two panels of experts. The first panel, which evaluated the priorities of the objectives and criteria in relationship to the mission, comprised five members of the Best Men’s Fashion (BMF) LLC executive team who were project team members acting on behalf of the company. These experts had direct knowledge of BMF’s strengths and weaknesses and could make decisions on what they thought would be best for the company. The second panel consisted of two external experts with significant cloud strategy experience. This panel was tasked with evaluating each of the strategies in relation to the third level criteria. Since they had no knowledge of BMF’s internal climate and (fictional) situation with IT staffing, they did not participate in the upper tier evaluation.
There were two rounds of analysis in the HDM modeling tool. The first round was negated as it took in all seven of the experts’ opinions into account for all tiers. This round was inconclusive in determining a cloud strategy, so their opinions were critiqued in class, revaluated by the team, and then redeveloped into a new strategy. The second round was crafted in the same way, with the experts divided into business and cloud expertise and who were only allowed to influence tiers on which they had extensive knowledge.
Scalability, Protection and Service Charges were top-ranked concerns among all the criteria in both the first and second rounds. As a result, the team is highly confident that these are the most important criteria a company should evaluate when choosing a cloud strategy.
The results of the second round were more conclusive when compared