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- Creators: Kellso, James
- Creators: Arizona State University
- Member of: Theses and Dissertations
Description
This dissertation is an exploratory study that examined the differences in perceptions about supply chain management strategy, topics, tools, and techniques between procurement professionals in public and private sector organizations. This was accomplished through a survey of procurement professionals in a Fortune 500 company and a municipality in Arizona. The data were analyzed to understand how perceptions of supply chain management differed within this sample and whether the differences in perceptions were associated with formal education levels. Key findings indicate that for this or similar samples, public procurement respondents viewed their organizations' approach to supply chain management as a narrow function within purchasing while private sector respondents viewed their organization's approach to supply chain management as a strategic purchasing perspective that requires the coordination of cross functional areas. Second, public procurement respondents reported consistent and statistically significant lower levels of formal education than private sector respondents. Third, the supply chain management topics, tools, and techniques seem to be more important to private sector respondents than the public sector respondents. Finally, Respondents in both sectors recognize the importance of ethics and ethical behavior as an essential part of supply chain management.
ContributorsHeller, Jacob (Author) / Cayer, Joseph (Thesis advisor) / Lan, Gerald (Committee member) / Eden, Catherine (Committee member) / Arizona State University (Publisher)
Created2013
Description
Today's competitive markets force companies to constantly engage in the complex task of managing their demand. In make-to-order manufacturing or service systems, the demand of a product is shaped by price and lead times, where high price and lead time quotes ensure profitability for supplier, but discourage the customers from placing orders. Low price and lead times, on the other hand, generally result in high demand, but do not necessarily ensure profitability. The price and lead time quotation problem considers the trade-off between offering high and low prices and lead times. The recent practices in make-to- order manufacturing companies reveal the importance of dynamic quotation strategies, under which the prices and lead time quotes flexibly change depending on the status of the system. In this dissertation, the objective is to model a make-to-order manufacturing system and explore various aspects of dynamic quotation strategies such as the behavior of optimal price and lead time decisions, the impact of customer preferences on optimal decisions, the benefits of employing dynamic quotation in comparison to simpler quotation strategies, and the benefits of coordinating price and lead time decisions. I first consider a manufacturer that receives demand from spot purchasers (who are quoted dynamic price and lead times), as well as from contract customers who have agree- ments with the manufacturer with fixed price and lead time terms. I analyze how customer preferences affect the optimal price and lead time decisions, the benefits of dynamic quo- tation, and the optimal mix of spot purchaser and contract customers. These analyses necessitate the computation of expected tardiness of customer orders at the moment cus- tomer enters the system. Hence, in the second part of the dissertation, I develop method- ologies to compute the expected tardiness in multi-class priority queues. For the trivial single class case, a closed formulation is obtained. For the more complex multi-class case, numerical inverse Laplace transformation algorithms are developed. In the last part of the dissertation, I model a decentralized system with two components. Marketing department determines the price quotes with the objective of maximizing revenues, and manufacturing department determines the lead time quotes to minimize lateness costs. I discuss the ben- efits of coordinating price and lead time decisions, and develop an incentivization scheme to reduce the negative impacts of lack of coordination.
ContributorsHafizoglu, Ahmet Baykal (Author) / Gel, Esma S (Thesis advisor) / Villalobos, Jesus R (Committee member) / Mirchandani, Pitu (Committee member) / Keskinocak, Pinar (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Supply chains are increasingly complex as companies branch out into newer products and markets. In many cases, multiple products with moderate differences in performance and price compete for the same unit of demand. Simultaneous occurrences of multiple scenarios (competitive, disruptive, regulatory, economic, etc.), coupled with business decisions (pricing, product introduction, etc.) can drastically change demand structures within a short period of time. Furthermore, product obsolescence and cannibalization are real concerns due to short product life cycles. Analytical tools that can handle this complexity are important to quantify the impact of business scenarios/decisions on supply chain performance. Traditional analysis methods struggle in this environment of large, complex datasets with hundreds of features becoming the norm in supply chains. We present an empirical analysis framework termed Scenario Trees that provides a novel representation for impulse and delayed scenario events and a direction for modeling multivariate constrained responses. Amongst potential learners, supervised learners and feature extraction strategies based on tree-based ensembles are employed to extract the most impactful scenarios and predict their outcome on metrics at different product hierarchies. These models are able to provide accurate predictions in modeling environments characterized by incomplete datasets due to product substitution, missing values, outliers, redundant features, mixed variables and nonlinear interaction effects. Graphical model summaries are generated to aid model understanding. Models in complex environments benefit from feature selection methods that extract non-redundant feature subsets from the data. Additional model simplification can be achieved by extracting specific levels/values that contribute to variable importance. We propose and evaluate new analytical methods to address this problem of feature value selection and study their comparative performance using simulated datasets. We show that supply chain surveillance can be structured as a feature value selection problem. For situations such as new product introduction, a bottom-up approach to scenario analysis is designed using an agent-based simulation and data mining framework. This simulation engine envelopes utility theory, discrete choice models and diffusion theory and acts as a test bed for enacting different business scenarios. We demonstrate the use of machine learning algorithms to analyze scenarios and generate graphical summaries to aid decision making.
ContributorsShinde, Amit (Author) / Runger, George C. (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Villalobos, Rene (Committee member) / Janakiram, Mani (Committee member) / Arizona State University (Publisher)
Created2012
Description
Social shopping has emerged as a popular online retailing segment. Social shopping revolves around online communities that bring consumers together to shop for deals. Online retailers have been making significant investments to encourage consumers to join online communities linked to their websites in the hope that social interactions among consumers will increase consumption rates. However, the assumption that social interactions increase consumption rates in social shopping remains largely untested in empirical settings. Also, the mechanisms of such an effect remain unclear. Moreover, extant literature has overlooked the role played by elements of the marketing mix, including product characteristics and the commercial context, in defining the effect that social interaction mechanisms have on consumption rates in this focused context. Furthermore, common knowledge in the operations management discipline challenges the largely held assumption, in the social interactions literature, that increasing consumption rates will always be beneficial to online retailers. Higher consumption rates may lead to stockouts, leading to lower service levels. This dissertation develops and empirically tests a theoretical framework that addresses these managerially relevant issues. Specifically, the investigation centers on the effects of social interaction mechanisms on consumption rates in social shopping. In turn, it assesses the nature of the relationship between consumption rates and service levels, after controlling for inventory provision. Finally, it assesses the role played by elements of the marketing mix in defining the relationship between social interaction mechanisms and consumption rates in this focused context. The research methodology uses experiments as the primary source of data collection, and employs econometrics techniques to statistically assess the conceptual framework. The results from the empirical analysis provide interesting insights. First, they unveil influential consumers in social shopping according to relational and structural elements of the social network of consumers and time of purchase. Second, the influence of early buyers' purchases on consumption rates becomes weaker when the quality of the products being offered as part of a deal increases, but it becomes stronger when the price of those products increases. Finally, as deals' consumption rates increase, their service levels decrease at a faster pace.
ContributorsSodero, Annibal (Author) / Rabinovich, Elliot (Thesis advisor) / Sinha, Rajiv (Committee member) / Maltz, Arnold (Committee member) / Arizona State University (Publisher)
Created2012
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 paper outlines the process of designing, creating, and implementing a supply chain management outreach program to benefit high schools students in areas surrounding Intel campuses. The program—which spreads awareness of supply chain management and STEM (Science, Technology, Engineering, Math) and how they work together in businesses today—was created and tested by me, with the help of the following committee members: James Kellso – Director, Cheryl Dalsin – 2nd Reader, and Jack Berg – 3rd Reader. The end goal is for this program to become sustainable, and for it to spread as far and wide as possible. Supply chain management and STEM are becoming crucial to understand in businesses today and will only become more imperative in future years.
Keywords: supply chain management (SCM), Science Technology Engineering Math (STEM)
Keywords: supply chain management (SCM), Science Technology Engineering Math (STEM)
ContributorsHughes, Kelsey Ellen (Author) / Kellso, James (Thesis director) / Dalsin, Cheryl (Committee member) / Berg, Jack (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / Department of Supply Chain Management (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
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
This thesis looks at a short-term solution to the truck driver shortage: transitioning U.S. military veterans into truck driver roles. Due to the adoption of self-driving trucks, the shortage is projected to end in 2022; however, freight companies may not be able to keep up with growing freight volumes until then. In the meantime, providing commercial driver's license (CDL) training on military bases has the potential to alleviate the shortage and veteran unemployment. A number of journal articles were read and interviews were conducted to determine the practicality of this solution. This thesis includes those findings and a number of considerations that should be made before implementing it.
ContributorsPatel, Nikhil (Author) / Kellso, James (Thesis director) / Maltz, Arnold (Committee member) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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
The original goal of this project was to create a case study that would help figure out a way to figure out how to get better food, and more food, to areas where there is little to no logistical infrastructure in place. Specifically, the Navajo Nation in North Eastern Arizona where the road infrastructure is not as developed and without enough stores to saturate the region. A partnership with Peddler's Son Produce, a company who was hoping to expand their distribution services to North-Eastern Arizona and other lesser-served areas across Arizona, allowed for the creation of Logistical Route Simulations which allowed the expanse of what areas could be reached with cross-docking stations in various areas. After all the information of the route simulations was compiled, it was abstracted to a case study. There is no one solution of how to expand a company so what the case study does is give students all of the information for costs and potential routes and then tells them to decide how many stops should be taken at each city in each route, which routes should be taken, and which routes shouldn't, and which cross-docking station, or multiple cross-docking stations the company should choose. The Case Study also includes teaching notes for the professor doing it which have the completed logistic route simulations and all the data and information that was learned but not included in the case study. This case study can now be used to help others figure out how to create profitable logistics routes which serves the original goal of the project.
ContributorsFierro, Leticia (Author) / Maltz, Arnold (Thesis director) / Kellso, James (Committee member) / Department of Supply Chain Management (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05