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- Creators: Brahms, Johannes, 1833-1897
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
Description
The purpose of this thesis research project is to explore blockchain technology and its present and future applications within supply chain management. Emerging blockchain technologies, both public and private, are already showing great promise for a number of applications in and outside supply chain management. Our sole focus is to understand the fundamentals of blockchain, smart contracts, current applications in supply chain, and the future possibilities for blockchain to shape global supply chains. Many have theorized about how private blockchains can be implemented and used; however, there is little research to date that has collected and explored the actual use cases in industry today. The mission of this research paper is to separate theory from the current state of the technology and provide a clearer understanding of where the technology is headed in the near future. We aim to produce a work that will provide a comprehensive description and commentary on current use cases for the education of students and industry professionals alike. With any new technological developments, terminology and technicalities can be paralyzing, and this is particularly true for blockchain technology. For this project, our goal was to create a document that cuts through the complexities and allows a non-technical audience to gain a strong foundational understanding of blockchain's potential and current limitations within supply chains. Provided this, some highly technical concepts and implementation details will not be explored due to the complexity and minimal understanding even amongst industry experts. As future supply chain professionals, we are motivated to further our understanding of blockchain technologies and the potential for this technology to shape the future of supply chain management.
ContributorsBecker, Logan (Co-author) / Falco, Alexander (Co-author) / Murphy, Thomas Brian (Co-author) / Taylor, Todd (Thesis director) / Wiedmer, Robert (Committee member) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
P.F. Chang's China Bistro is a privately-held purveyor of Asian fare in the United States and internationally, known largely for its vibrant atmosphere and lettuce wraps. With hundreds of locations and dozens of menu items, procurement, logistics, and coordination of ingredient delivery to P.F. Chang's restaurants is no small task. Despite their difficulty, supply chain operations from suppliers to customers' plates must run efficiently if P.F. Chang's is to maintain customer loyalty, a trusted brand, and profitability. As such, supply chain initiatives that allow for faster, better, or lower-cost operation are valuable investments for P.F. Chang's. In this project, two initiatives focused on increasing visibility along the value chain (with the hope of creating immediate value and easier implementation for future strategies). The first initiative involved stakeholder interviews and academic research to determine evaluation methods for P.F. Chang's suppliers in the form of a scorecard. The second project required extensive data collection from suppliers to isolate and remove excess cost in the inbound logistics of P.F. Chang's inventory. Both initiatives led to incremental improvement at P.F. Changs and the latter provided substantial cost savings. Further investigation and work is likely to yield continued benefits for the company. The increased use of data in all supply chains to guide decision-making will be easier for P.F. Chang's as it manages ongoing visibility efforts. Although process explanation and general outcomes will be reported here, the proprietary nature of P.F. Chang's data precludes full disclosure of the project results in public documentation.
ContributorsBarger, Michael Richard (Author) / Taylor, Todd (Thesis director) / Miller, Steve (Committee member) / Department of Economics (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
ContributorsBrahms, Johannes, 1833-1897 (Composer)
Description
The purpose of this thesis is to gain a greater understanding of Ph. D research and how general research in the field of supply chain management and operations is being conducted in 2017. In order to gain a greater understanding, this thesis contains summaries and personal perspectives on four different supply chain management and operations seminars from visiting professors. There is also an expanded examination of the research area from the fourth seminar, process compliance. Multiple literature sources were used to construct a perspective on process development, process standardization, and process compliance origins and current state.
ContributorsBerg, Paul Joseph (Author) / Taylor, Todd (Thesis director) / Printezis, Antonios (Committee member) / Department of Finance (Contributor) / Hugh Downs School of Human Communication (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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