Matching Items (35)
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- All Subjects: Supply Chain Management
- Creators: Department of Information Systems
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
This piece aims to discuss the roles of emerging geographies within the context of global supply chains, approaching the conversation with a "systems" view, emphasizing three key facets essential to a holistic and interdisciplinary environmental analysis: -The Implications of Governmental & Economic Activities -Supply Chain Enablement Activities, Risk Mitigation in Emerging Nations -Implications Regarding Sustainability, Corporate Social Responsibility In the appreciation of the interdisciplinary implications that stem from participation in global supply networks, supply chain professionals can position their firms for continued success in the proactive construction of robust and resilient supply chains. Across industries, how will supply networks in emerging geographies continue to evolve? Appreciating the inherent nuances related to the political and economic climate of a region, the extent to which enablement activities must occur, and sustainability/CSR tie-ins will be key to acquire this understanding. This deliverable aims to leverage the work of philosophers, researchers and business personnel as these questions are explored. The author will also introduce a novel method of teaching (IMRS) in the undergraduate business classroom that challenges the students to integrate their prior experiences both in the classroom and in the business world as they learn to craft locally relevant solutions to solve complex global problems.
ContributorsVaney, Rachel Lee (Author) / Maltz, Arnold (Thesis director) / Kellso, James (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor)
Created2015-05
Description
This report details a prioritization value model that was created for the use of Arizona State University and ASU LightWorks in determining and implementing appropriate sustainability projects for removing greenhouse gas emissions. A thorough review regarding the current project selection process, and an extensive analysis into the desired state of the process was conducted for this paper. The newly developed prioritization model includes multiple attributes that rank and prioritize projects based upon the highest value as determined by criteria set forth by the university. Encompassed within this report are the steps in creating the decision model, as well as the benefits and additional uses of the model for the end user. From the analysis and model created, the end user has the ability to choose carbon neutral projects that better align with the vision of the New American University.
ContributorsAmoroso, Nicholas (Co-author) / Lee, Betty (Co-author) / Brooks, Dan (Thesis director) / Johnson, Travis (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor)
Created2015-05
Description
New Venture Group, a student-run consulting organization at ASU, collaborated with representatives from Intel Corporation to determine current best supplier management practices in the area of capital equipment procurement. The New Venture Group team accomplished this goal by completing the following deliverables: (1) Research and consolidate best practices for managing capital equipment suppliers. (2) Interview suppliers of capital equipment in the semiconductor industry to understand their motivators. (3) Examine top supply chain companies that utilize capital equipment manufacturers within their procurement systems. (4) Gather data and knowledge in conjunction with Intel Corporation's current practices to improve the effectiveness of the company's supplier management techniques regarding capital equipment manufacturers. The thesis report outlines the key insights and recommendations that our team extracted from the research that we performed. Our team analyzed peer-reviewed journal articles, conducted interviews with suppliers of capital equipment to semiconductor manufacturers, and surveyed buyers at top companies to reach important key insights. We then used these insights to develop the following strategies to improve Intel's capital equipment supplier management structure: All Suppliers 1. Allow high-performance suppliers to select one reward from an established portfolio of incentives. 2. Increase measurement frequency for specific metrics. 3. Use collaborative two-way measurement with a corresponding balanced scorecard. Key Suppliers of Critical Products 4. Conduct gap analysis through supplier self-assessments. 5. Implement collaborative target pricing. 6. Delegate an Ombudsman. 7. Create a value map to determine the strengths and incentivize collaboration. 8. Create comparison charts comparing supplier technological competencies versus Intel's product developments. 9. Establish a systematized product development process and strategic sourcing strategy that supports the continuation of Moore's Law.
ContributorsSantiago, Bryce (Co-author) / Chen, Jenny (Co-author) / Chang, Karen (Co-author) / Baldridge, Stephen (Co-author) / Laub, Jeffrey (Thesis director) / Brooks, Daniel (Committee member) / Department of Information Systems (Contributor, Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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
The purpose of this project is to provide our client with a tool to mitigate Company X's franchise-wide inventory control problem. The problem stems from the franchises' initial strategy to buy all inventory as customers brought them in without a quantitative way for buyers to evaluate the store's inventory needs. The Excel solution created by our team serves to provide that evaluation for buyers using deseasonalized linear regression to forecast inventory needs for clothing of different sizes and seasons by month. When looking at the provided sales data from 2014-2016, there was a clear seasonal trend, so the appropriate forecasting model was determined by testing 3 models: Triple Exponential Smoothing model, Deseasonalized Simple Linear Regression, and Multiple Linear Regression.The model calculates monthly optimal inventory levels (current period plus future 2 periods of inventory). All of the models were evaluated using the lowest mean absolute error (meaning best fit with the data), and the model with best fit was Deseasonalized Simple Linear Regression, which was then used to build the Excel tool. Buyers can use the Excel tool built with this forecasting model to evaluate whether or not to buy a given item of any size or season. To do this, the model uses the previous year's sales data to forecast optimal inventory level and compares it to the stores' current inventory level. If the current level is less than the optimal level, the cell housing current value will turn green (buy). If the currently level is greater than or equal to optimal level or less than optimal inventory level*1.05, current value will turn yellow (buy only if good quality). If the current level is greater than optimal level*1.05 current level will be red (don't buy). We recommend both stores implement a way of keeping track of how many clothing items held in each bin to keep more accurate inventory count. In addition, the model's utility will be of limited use until both stores' inventories are at a level where they can afford to buy. Therefore, it is in the client's best interest to liquidate stale inventor into store credit or cash In the future, the team would also like to develop a pricing model to better meet the needs of the client's two locations.
ContributorsUribes-Yanez, Diego (Co-author) / Liu, Jessica (Co-author) / Taylor, Todd (Thesis director) / Gentile, Erica (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Cognitive technology has been at the forefront of the minds of many technology, government, and business leaders, because of its potential to completely revolutionize their fields. Furthermore, individuals in financial statement auditor roles are especially focused on the impact of cognitive technology because of its potential to eliminate many of the tedious, repetitive tasks involved in their profession. Adopting new technologies that can autonomously collect more data from a broader range of sources, turn the data into business intelligence, and even make decisions based on that data begs the question of whether human roles in accounting will be completely replaced. A partial answer: If the ramifications of past technological advances are any indicator, cognitive technology will replace some human audit operations and grow some new and higher order roles for humans. It will shift the focus of accounting professionals to more complex judgment and analysis.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
ContributorsWitkop, David (Author) / Dawson, Gregory (Thesis director) / Munshi, Perseus (Committee member) / School of Accountancy (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The main compelling question to this thesis was to determine if there is a relationship between the amount of sensitivity received in ones college experience to how easily one transitions to a full time role upon graduation. Furthermore to determine if there is measurable difference, what can educators do to close the gap to better serve students. The conduction of this thesis was done through a survey via Google Forms targeting three groups. The three groups were Alpha Kappa Psi at Arizona State University, Delta Sigma Pi at Penn State University and the Supply Chain Development Program at Dell in Austin, Texas. These groups allowed for a wide range of demographics in participants from all over the US and with many different business majors. There were two main sections in the survey, personal experiences with professors and personal experiences with peers. Both asked multiple different hard data questions (multiple choice, numerical rating, drop down) and short answer questions (open ended.) The goal was to gauge participant's experiences with their professors and their peers in terms of sensitivity and see if it helped or hindered their experience transitioning to a full time role. The results for the hard data indicated that there was a significant correlation between better professors being more sensitive and worse professors exercising very little sensitivity. The open ended responses indicated that students preferred professors that gave less sensitive and academic approach and more real life experiences to help them transition to their job. There were many issues to if the open-ended responses specifically addressed sensitivity versus other topics. Three other topics that were clearly alternately identified were class behavior, job relevancy, and professor influence/resistance. Overall from the research completed in this study it can be concluded that sensitivity does not significantly affect the performance in the transition from college to working in a profession environment.
ContributorsGhinos, Christina Eva (Author) / Kellso, James (Thesis director) / Thorn, Taylor (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This thesis, through a thorough literature and content review, discusses the various ways that data analytics and supply chain management intersect. Both fields have been around for a while, but are incredibly aided by the information age we live in today. Today's ERP systems and supply chain software packages use advanced analytic techniques and algorithms to optimize every aspect of supply chain management. This includes aspects like inventory optimization, portfolio management, network design, production scheduling, fleet planning, supplier evaluation, and others. The benefit of these analytic techniques is a reduction in costs as well as an improvement in overall supply chain performance and efficiencies. The paper begins with a short historical context on business analytics and optimization then moves on to the impact and application of analytics in the supply chain today. Following that the implications of big data are explored, along with how a company might begin to take advantage of big data and what challenges a firm may face along the way. The current tools used by supply chain professionals are then discussed. There is then a section on the most up and coming technologies; the internet of things, blockchain technology, additive manufacturing (3D printing), and machine learning; and how those technologies may further enable the successful use of analytics to improve supply chain management. Companies that do take advantage of analytics in their supply chains are sure to maintain a competitive advantage over those firms that fail to do so.
ContributorsCotton, Ryan Aaron (Author) / Taylor, Todd (Thesis director) / Arora, Hina (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
During the summer of 2016 I had an internship in the Fab Materials Planning group (FMP) at Intel Corporation. FMP generates long-range (6-24 months) forecasts for chemical and gas materials used in the chip fabrication process. These forecasts are sent to Commodity Mangers (CMs) in a separate department where they communicate the forecast and any constraints to Intel suppliers. The intern manager of the group, Scott Keithley, created a prototype of a model to redefine how FMP determines which materials require a forecast update (forecasting cadence). However, the model prototype was complex to use, not intuitive, and did not receive positive feedback from the rest of the team or external stakeholders. This thesis will detail the steps I took in identifying the main problem the model was intended to address, how I approached the problem, and some of the major iterations I took to modify the model. It will also go over the final model dashboard and the results of the model use and integration. An improvement analysis and the intended and unintended consequences of the model will also be included. The results of this model demonstrate that statistical process control, a traditionally operational analysis, can be used to generate a forecasting cadence. It will also verify that an intuitive user interface is vital to the end user adoption and integration of an analytics based model into an established process flow. This model will generate an estimated time savings of 900 hours per year as well as giving FMP the ability to be more proactive in its forecasting approach.
ContributorsMatson, Rilee Nicole (Author) / Kellso, James (Thesis director) / Keithley, Scott (Committee member) / Department of Supply Chain Management (Contributor) / Department of Information Systems (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