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- Creators: Department of Information Systems
- Creators: Tsai, Wei-Tek
Description
A new algebraic system, Test Algebra (TA), is proposed for identifying faults in combinatorial testing for SaaS (Software-as-a-Service) applications. In the context of cloud computing, SaaS is a new software delivery model, in which mission-critical applications are composed, deployed, and executed on cloud platforms. Testing SaaS applications is challenging because new applications need to be tested once they are composed, and prior to their deployment. A composition of components providing services yields a configuration providing a SaaS application. While individual components
in the configuration may have been thoroughly tested, faults still arise due to interactions among the components composed, making the configuration faulty. When there are k components, combinatorial testing algorithms can be used to identify faulty interactions for t or fewer components, for some threshold 2 <= t <= k on the size of interactions considered. In general these methods do not identify specific faults, but rather indicate the presence or absence of some fault. To identify specific faults, an adaptive testing regime repeatedly constructs and tests configurations in order to determine, for each interaction of interest, whether it is faulty or not. In order to perform such testing in a loosely coupled distributed environment such as
the cloud, it is imperative that testing results can be combined from many different servers. The TA defines rules to permit results to be combined, and to identify the faulty interactions. Using the TA, configurations can be tested concurrently on different servers and in any order. The results, using the TA, remain the same.
in the configuration may have been thoroughly tested, faults still arise due to interactions among the components composed, making the configuration faulty. When there are k components, combinatorial testing algorithms can be used to identify faulty interactions for t or fewer components, for some threshold 2 <= t <= k on the size of interactions considered. In general these methods do not identify specific faults, but rather indicate the presence or absence of some fault. To identify specific faults, an adaptive testing regime repeatedly constructs and tests configurations in order to determine, for each interaction of interest, whether it is faulty or not. In order to perform such testing in a loosely coupled distributed environment such as
the cloud, it is imperative that testing results can be combined from many different servers. The TA defines rules to permit results to be combined, and to identify the faulty interactions. Using the TA, configurations can be tested concurrently on different servers and in any order. The results, using the TA, remain the same.
ContributorsQi, Guanqiu (Author) / Tsai, Wei-Tek (Thesis advisor) / Davulcu, Hasan (Committee member) / Sarjoughian, Hessam S. (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2014
Description
Company X is one of the world's largest manufacturer of semiconductors. The company relies on various suppliers in the U.S. and around the globe for its manufacturing process. The financial health of these suppliers is vital to the continuation of Company X's business without any material interruption. Therefore, it is in Company X's interest to monitor its supplier's financial performance. Company X has a supplier financial health model currently in use. Having been developed prior to watershed events like the Great Recession, the current model may not reflect the significant changes in the economic environment due to these events. Company X wants to know if there is a more accurate model for evaluating supplier health that better indicates business risk. The scope of this project will be limited to a sample of 24 suppliers representative of Company X's supplier base that are public companies. While Company X's suppliers consist of both private and public companies, the used of exclusively public companies ensures that we will have sufficient and appropriate data for the necessary analysis. The goal of this project is to discover if there is a more accurate model for evaluating the financial health of publicly traded suppliers that better indicates business risk. Analyzing this problem will require a comprehensive understanding of various financial health models available and their components. The team will study best practice and academia. This comprehension will allow us to customize a model by incorporating metrics that allows greater accuracy in evaluating supplier financial health in accordance with Company X's values.
ContributorsLi, Tong (Co-author) / Gonzalez, Alexandra (Co-author) / Park, Zoon Beom (Co-author) / Vogelsang, Meridith (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
DescriptionThe thesis will study price optimization techniques, SaaS industry pricing structures, A/B testing, and then build a unique framework to optimize price and maximize revenue. The ultimate goal of the thesis research is to create a framework that identifies the best pricing structure and price points for a SaaS company.
ContributorsRyu, Kibaek (Author) / Clark, Joseph (Thesis director) / Granberry, Chase (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor)
Created2014-05
Description
Amazon Prime Air is the innovative new service that promises automated drone delivery in thirty minutes or less. The platform has not yet been brought to market, but there is a plethora compelling data available that suggests it will be a unique and highly disruptive business segment for Amazon. The aim of this thesis is to analyze the framework laid out by Amazon.com, Inc. for their anticipated Prime Air drone delivery platform, and offer our recommendations for what steps the e-commerce giant should take moving forward. Following a brief recap of the company's founding and a breakdown of its various business segments, we will begin our analysis by examining past strategic decisions that Amazon has made which have directly contributed to their current market position. It is our goal to construct a narrative of what events lead the company to begin developing a fleet of automated delivery vehicles. Following this history lesson, we will review and criticize the existing elements of Amazon's Prime Air platform, and explore any possible alternatives that they could have taken to optimize the development of this exciting new technology. Criticisms will touch upon elements such as cost efficiencies, brand management, and utilization of infrastructure to name but a few. These criticisms will be based upon data sourced from Amazon's available material as well as comments from market analysts and journalists. The culminating element of our analysis will be to offer our professional recommendations as to what we believe the next logical steps that Amazon should take for their Prime Air platform. These recommendations will be informed by our criticisms and our understanding of Amazon as a corporation. This chapter will be largely concerned with guiding Amazon towards a fully optimized drone delivery platform. Our recommendations will be based upon our extensive experience concerning cost and logistical efficiencies, as well as our knowledge of Amazon as a corporation. We will offer succinct suggestions for Amazon's immediate needs as well as long-term solutions to lingering obstacles that they may face.
ContributorsMcCaleb, Nicholas (Co-author) / Glynn, Reagan (Co-author) / Choi, Thomas (Thesis director) / Rogers, Dale (Committee member) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Goal of paper: To discuss the benefits and detractors of asteroid mining, and whether this is a task that should be undertaken now, or if something needs to change before real strides can be made in the field. Findings: After research and looking at what companies are currently doing, I have found several different benefits and detractors of asteroid mining. The main benefit of asteroid mining is acquiring the resources at the end of the project, whether those resources are raw metals being brought back to Earth or water that will be used as fuel for deep space travel. Those resources are extremely valuable and can create a huge profit for the company that acquires them. However, these resources can take an extremely long time to acquire, at least 20 years. So, while this industry can be extremely lucrative, it may take quite a long time and will need plenty of funding and side ventures to stay afloat long enough to reach that goal. Overall, if financed properly asteroid mining can be extremely profitable.
ContributorsScheven, Spenser (Author) / Choi, Thomas (Thesis director) / Printezis, Antonios (Committee member) / Department of Information Systems (Contributor) / W. P. Carey School of Business (Contributor) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
In this paper, I analyze the pharmaceutical supply chain to identify the main causes of drug surplus. The main example I use throughout the paper is the current opioid epidemic, which has resulted in thousands of fatalities, caused by overdoses. After researching the industry players and their relationships in the supply chain, I have identified four main causes of drug surplus: the consolidation of pharmaceutical corporations with third-party manufacturers, along with consolidation within the wholesaler industry; the inappropriate pricing of opioid-based prescriptions negotiated by pharmacy benefit managers (PBMs); the significant influence of pharmaceutical corporations on physicians, leading to potentially unethical practices; and lastly patients openly distributing leftover prescriptions to the market, and looking for prescriptions elsewhere. To alleviate the drug surplus issue, I provide three solutions: implement both blockchain and reverse logistics into the pharmaceutical supply chain, improving transparency, and allowing patients to return incomplete prescriptions; and research the consolidation of PBMs with providers (hospital systems, clinics, etc.) to increase buyer power and appropriately price opioid-based prescriptions.
ContributorsRutkowski, Sarah (Author) / Helm, Jonathan (Thesis director) / Wiedmer, Robert (Committee member) / Department of Information Systems (Contributor) / W.P. Carey School of Business (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The goal of this thesis was to provide in depth research into the semiconductor wet-etch market and create a supplier analysis tool that would allow Company X to identify the best supplier partnerships. Several models were used to analyze the wet etch market including Porter's Five Forces and SWOT analyses. These models were used to rate suppliers based on financial indicators, management history, market share, research and developments spend, and investment diversity. This research allowed for the removal of one of the four companies in question due to a discovered conflict of interest. Once the initial research was complete a dynamic excel model was created that would allow Company X to continually compare costs and factors of the supplier's products. Many cost factors were analyzed such as initial capital investment, power and chemical usage, warranty costs, and spares parts usage. Other factors that required comparison across suppliers included wafer throughput, number of layers the tool could process, the number of chambers the tool has, and the amount of space the tool requires. The demand needed for the tool was estimated by Company X in order to determine how each supplier's tool set would handle the required usage. The final feature that was added to the model was the ability to run a sensitivity analysis on each tool set. This allows Company X to quickly and accurately forecast how certain changes to costs or tool capacities would affect total cost of ownership. This could be heavily utilized during Company X's negotiations with suppliers. The initial research as well the model lead to the final recommendation of Supplier A as they had the most cost effective tool given the required demand. However, this recommendation is subject to change as demand fluctuates or if changes can be made during negotiations.
ContributorsSchmitt, Connor (Co-author) / Rickets, Dawson (Co-author) / Castiglione, Maia (Co-author) / Witten, Forrest (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The aim of this thesis is to improve the user experience within FedEx's eProcurement system, directly address feedback received from customer surveys, and to make recommendations for the Sourcing and Procurement Division within FedEx. In the first part, the overall client engagement is outlined with the specific timeline between New Venture Group and FedEx. The thesis encompasses three deliverables that were integral parts to the semester-long consulting engagement. The thesis then dives into methodology and each deliverable individually. After months of conference calls and best practice research, consulting efforts are summarized in the results. In a detailed discussion sections, the thesis forecasts opportunities for FedEx within sourcing and procurement. Here, the thesis draws on sources from various companies and research. Furthermore, overall recommendations are given to FedEx and acknowledgements are made. In conclusion, the thesis hopes to offer FedEx improvements to leverage improved functionality of eProcurement that will become available in the next upgrade of the Performance Management System.
ContributorsRuhlman, Payne (Co-author) / Pollack, Amanda (Co-author) / Peterson, Andrew (Co-author) / Taylor, Todd (Thesis director) / Choi, Thomas (Committee member) / Halvorson, Joel (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor) / Department of Economics (Contributor) / School of International Letters and Cultures (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Nowadays, Computing is so pervasive that it has become indeed the 5th utility (after water, electricity, gas, telephony) as Leonard Kleinrock once envisioned. Evolved from utility computing, cloud computing has emerged as a computing infrastructure that enables rapid delivery of computing resources as a utility in a dynamically scalable, virtualized manner. However, the current industrial cloud computing implementations promote segregation among different cloud providers, which leads to user lockdown because of prohibitive migration cost. On the other hand, Service-Orented Computing (SOC) including service-oriented architecture (SOA) and Web Services (WS) promote standardization and openness with its enabling standards and communication protocols. This thesis proposes a Service-Oriented Cloud Computing Architecture by combining the best attributes of the two paradigms to promote an open, interoperable environment for cloud computing development. Mutil-tenancy SaaS applicantions built on top of SOCCA have more flexibility and are not locked down by a certain platform. Tenants residing on a multi-tenant application appear to be the sole owner of the application and not aware of the existence of others. A multi-tenant SaaS application accommodates each tenant’s unique requirements by allowing tenant-level customization. A complex SaaS application that supports hundreds, even thousands of tenants could have hundreds of customization points with each of them providing multiple options, and this could result in a huge number of ways to customize the application. This dissertation also proposes innovative customization approaches, which studies similar tenants’ customization choices and each individual users behaviors, then provides guided semi-automated customization process for the future tenants. A semi-automated customization process could enable tenants to quickly implement the customization that best suits their business needs.
ContributorsSun, Xin (Author) / Tsai, Wei-Tek (Thesis advisor) / Xue, Guoliang (Committee member) / Davulcu, Hasan (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Cloud computing has received significant attention recently as it is a new computing infrastructure to enable rapid delivery of computing resources as a utility in a dynamic, scalable, and visualized manner. SaaS (Software-as-a-Service) provide a now paradigm in cloud computing, which goal is to provide an effective and intelligent way to support end users' on-demand requirements to computing resources, including maturity levels of customizable, multi-tenancy and scalability. To meet requirements of on-demand, my thesis discusses several critical research problems and proposed solutions using real application scenarios. Service providers receive multiple requests from customers, how to prioritize those service requests to maximize the business values is one of the most important issues in cloud. An innovative prioritization model is proposed, which uses different types of information, including customer, service, environment and workflow information to optimize the performance of the system. To provide "on-demand" services, an accurate demand prediction and provision become critical for the successful of the cloud computing. An effective demand prediction model is proposed, and applied to a real mortgage application. To support SaaS customization and fulfill the various functional and quality requirements of individual tenants, a unified and innovative multi-layered customization framework is proposed to support and manage the variability of SaaS applications. To support scalable SaaS, a hybrid database design to support SaaS customization with two-layer database partitioning is proposed. To support secure SaaS, O-RBAC, an ontology based RBAC (Role based Access Control) model is used for Multi-Tenancy Architecture in clouds. To support a significant number of tenants, an easy to use SaaS construction framework is proposed. As a summary, this thesis discusses the most important research problems in cloud computing, towards effective and intelligent SaaS. The research in this thesis is critical to the development of cloud computing and provides fundamental solutions to those problems.
ContributorsShao, Qihong (Author) / Tsai, Wei-Tek (Thesis advisor) / Askin, Ronald (Committee member) / Ye, Jieping (Committee member) / Naphade, Milind (Committee member) / Arizona State University (Publisher)
Created2011