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- Creators: Barrett, The Honors College
Description
Energy is a central concern of sustainability because how we produce and consume energy affects society, economy, and the environment. Sustainability scientists are interested in energy transitions away from fossil fuels because they are nonrenewable, increasingly expensive, have adverse health effects, and may be the main driver of climate change. They see an opportunity for developing countries to avoid the negative consequences fossil-fuel-based energy systems, and also to increase resilience, by leap-frogging-over the centralized energy grid systems that dominate the developed world. Energy transitions pose both challenges and opportunities. Obstacles to transitions include 1) an existing, centralized, complex energy-grid system, whose function is invisible to most users, 2) coordination and collective-action problems that are path dependent, and 3) difficulty in scaling up RE technologies. Because energy transitions rely on technological and social innovations, I am interested in how institutional factors can be leveraged to surmount these obstacles. The overarching question that underlies my research is: What constellation of institutional, biophysical, and social factors are essential for an energy transition? My objective is to derive a set of "design principles," that I term institutional drivers, for energy transitions analogous to Ostrom's institutional design principles. My dissertation research will analyze energy transitions using two approaches: applying the Institutional Analysis and Development Framework and a comparative case study analysis comprised of both primary and secondary sources. This dissertation includes: 1) an analysis of the world's energy portfolio; 2) a case study analysis of five countries; 3) a description of the institutional factors likely to promote a transition to renewable-energy use; and 4) an in-depth case study of Thailand's progress in replacing nonrenewable energy sources with renewable energy sources. My research will contribute to our understanding of how energy transitions at different scales can be accomplished in developing countries and what it takes for innovation to spread in a society.
ContributorsKoster, Auriane Magdalena (Author) / Anderies, John M (Thesis advisor) / Aggarwal, Rimjhim (Committee member) / Van Der Leeuw, Sander (Committee member) / Arizona State University (Publisher)
Created2013
Description
As climate change and air pollution continue to plague the world today, committed citizens are doing their part to minimize their environmental impact. However, financial limitations have hindered a majority of individuals from adopting clean, renewable energy such as rooftop photovoltaic solar systems. England Sustainability Consulting plans to reverse this limitation and increase affordability for residents across Northern California to install solar panel systems for their energy needs. The purpose of this proposal is to showcase a new approach to procuring solar panel system components while offering the same products needed by each customer. We will examine market data to further prove the feasibility of this business approach while remaining profitable and spread our company's vision across all of Northern California.
ContributorsEngland, Kaysey (Author) / Dooley, Kevin (Thesis director) / Keahey, Jennifer (Committee member) / Department of Supply Chain Management (Contributor) / School of Social and Behavioral Sciences (Contributor) / W.P. Carey School of Business (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This work challenges the conventional perceptions surrounding the utility and use of the CMS Open Payments data. I suggest unconsidered methodologies for extracting meaningful information from these data following an exploratory analysis of the 2014 research dataset that, in turn, enhance its value as a public good. This dataset is favored for analysis over the general payments dataset as it is believed that generating transparency in the pharmaceutical and medical device R&D process would be of the greatest benefit to public health. The research dataset has been largely ignored by analysts and this may be one of the few works that have accomplished a comprehensive exploratory analysis of these data. If we are to extract valuable information from this dataset, we must alter both our approach as well as focus our attention towards re-conceptualizing the questions that we ask. Adopting the theoretical framework of complex systems serves as the foundation for our interpretation of the research dataset. This framework, in conjunction with a methodological toolkit for network analysis, may set a precedent for the development of alternative perspectives that allow for novel interpretations of the information that big data attempts to convey. By thus proposing a novel perspective in interpreting the information that this dataset contains, it is possible to gain insight into the emergent dynamics of the collaborative relationships that are established during the pharmaceutical and medical device R&D process.
ContributorsVelez-Cruz, Nayely Luz (Author) / Laubichler, Manfred (Thesis director) / Van Der Leeuw, Sander (Committee member) / School of Sustainability (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This study was conducted to better understand the making and measuring of renewable energy goals by the federal government. Three different energy types are studied: wind, solar, and biofuel, for two different federal departments: the Department of Defense and the Department of Energy. A statistical analysis and a meta-analysis of current literature will be the main pieces of information. These departments and energy types were chosen as they represent the highest potential for renewable energy production. It is important to understand any trends in goal setting by the federal government, as well as to understand what these trends represent in terms of predicting renewable energy production. The conclusion for this paper is that the federal government appears to set high goals for renewable energy initiatives. While the goals appear to be high, they are designed based on required characteristics described by the federal government. These characteristics are most often technological advancements, tax incentives, or increased production, with tax incentives having the highest priority. However, more often than not these characteristics are optimistic or simply not met. This leads to the resetting of goals before any goal can be evaluated, making it difficult to determine the goal-setting ability of the federal government.
ContributorsStapleton, Andrew (Co-author) / Charnell, Matthew (Co-author) / Printezis, Antonios (Thesis director) / Kull, Thomas (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor) / Department of Supply Chain Management (Contributor)
Created2015-05
Description
Twitter, the microblogging platform, has grown in prominence to the point that the topics that trend on the network are often the subject of the news and other traditional media. By predicting trends on Twitter, it could be possible to predict the next major topic of interest to the public. With this motivation, this paper develops a model for trends leveraging previous work with k-nearest-neighbors and dynamic time warping. The development of this model provides insight into the length and features of trends, and successfully generalizes to identify 74.3% of trends in the time period of interest. The model developed in this work provides understanding into why par- ticular words trend on Twitter.
ContributorsMarshall, Grant A (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Investment real estate is unique among similar financial instruments by nature of each property's internal complexities and interaction with the external economy. Where a majority of tradable assets are static goods within a dynamic market, real estate investments are dynamic goods within a dynamic market. Furthermore, investment real estate, particularly commercial properties, not only interacts with the surrounding economy, it reflects it. Alive with tenancy, each and every commercial investment property provides a microeconomic view of businesses that make up the local economy. Management of commercial investment real estate captures this economic snapshot in a unique abundance of untapped statistical data. While analysis of such data is undeniably valuable, the efforts involved with this process are time consuming. Given this unutilized potential our team has develop proprietary software to analyze this data and communicate the results automatically though and easy to use interface. We have worked with a local real estate property management and ownership firm, Reliance Management, to develop this system through the use of their current, historical, and future data. Our team has also built a relationship with the executives of Reliance Management to review functionality and pertinence of the system we have dubbed, Reliance Dashboard.
ContributorsBurton, Daryl (Co-author) / Workman, Jack (Co-author) / LePine, Marcie (Thesis director) / Atkinson, Robert (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Management (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
In the era of big data, the impact of information technologies in improving organizational performance is growing as unstructured data is increasingly important to business intelligence. Daily data gives businesses opportunities to respond to changing markets. As a result, many companies invest lots of money in big data in order to obtain adverse outcomes. In particular, analysis of commercial websites may reveal relations of different parties in digital markets that pose great value to businesses. However, complex ecommercial sites present significant challenges for primary web analysts. While some resources and tutorials of web analysis are available for studying, some learners especially entrylevel analysts still struggle with getting satisfying results. Thus, I am interested in developing a computer program in the Python programming language for investigating the relation between sellers’ listings and their seller levels in a darknet market. To investigate the relation, I couple web data retrieval techniques with doc2vec, a machine learning algorithm. This approach does not allow me to analyze the potential relation between sellers’ listings and reputations in the context of darknet markets, but assist other users of business intelligence with similar analysis of online markets. I present several conclusions found through the analysis. Key findings suggest that no relation exists between similarities of different sellers’ listings and their seller levels in rsClub Market. This study can become a great and unique example of web analysis and create potential values for modern enterprises.
ContributorsWang, Zhen (Author) / Benjamin, Victor (Thesis director) / Santanam, Raghu (Committee member) / Barrett, The Honors College (Contributor)
Created2018-05
Description
As the use of Big Data gains momentum and transitions into mainstream adoption, marketers are racing to generate valuable insights that can create well-informed strategic business decisions. The retail market is a fiercely competitive industry, and the rapid adoption of smartphones and tablets have led e-commerce rivals to grow at an unbelievable rate. Retailers are able to collect and analyze data from both their physical stores and e-commerce platforms, placing them in a unique position to be able to fully capitalize on the power of Big Data. This thesis is an examination of Big Data and how marketers can use it to create better experiences for consumers. Insights generated from the use of Big Data can result in increased customer engagement, loyalty, and retention for an organization. Businesses of all sizes, whether it be enterprise, small-to-midsize, and even solely e-commerce organizations have successfully implemented Big Data technology. However, there are issues regarding challenges and the ethical and legal concerns that need to be addressed as the world continues to adopt the use of Big Data analytics and insights. With the abundance of data collected in today's digital world, marketers must take advantage of available resources to improve the overall customer experience.
ContributorsHaghgoo, Sam (Author) / Ostrom, Amy (Thesis director) / Giles, Bret (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / W. P. Carey School of Business (Contributor) / Department of Management (Contributor)
Created2014-05
Description
The global energy demand is expected to grow significantly in the next several decades and support for energy generation with high carbon emissions is continuing to decline. Alternative methods have gained interest, and wind energy has established itself as a viable source. Standard wind farms have limited room for growth and improvement, so wind energy has started to explore different directions. The urban environment is a potential direction for wind energy due to its proximity to the bulk of energy demand. CFD analysis has demonstrated that the presence of buildings can accelerate wind speeds between buildings and on rooftops. However, buildings generate areas of increased turbulence at their surface. The turbulence thickness and intensity vary with roof shape, building height, and building orientation. The analysis has concluded that good wind resource is possible in the urban environment in specific locations. With that, turbine selection becomes very important. A comparison has concluded that vertical axis wind turbines are more useful in the urban environment than horizontal axis wind turbines. Furthermore, building-augmented wind turbines are recommended because they are architecturally integrated into a building for the specific purpose of generating more energy. The research has concluded that large-scale generation in the urban environment is unlikely to be successful, but small-scale generation is quite viable. Continued research and investigation on urban wind energy is recommended.
ContributorsKlumpers, Ryan Scott (Author) / Calhoun, Ronald (Thesis director) / Huang, Huei-Ping (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
Description
There is an increasing need to understand and develop clean cooking technologies in low- and middle-income countries (LMICs). The provision of clean energy where modern energy is not available is important in advancing the 17 sustainable development goals as set by the United Nations. Green charcoal is a cooking fuel technology made from ground and compressed biochar, an organic material made from heating a feedstock (biomass, forest residues, agriculture waste, invasive species, etc.) in an oxygen deprived environment to high temperatures. Green charcoal behaves similarly to wood charcoal or coal but is different from these energy products in that it is produced from biomass, not from wood or fossil fuels. Green charcoal has gained prominence as a cooking fuel technology in South-East Asia recently. Within the context of Nepal, green charcoal is currently being produced using lantana camara, an invasive species in Nepal, as a feedstock in order to commoditize the otherwise destructive plant. The purpose of this study was to understand the innovation ecosystem of green charcoal within the context of Nepal’s renewable energy sector. An innovation ecosystem is all of the actors, users and conditions that contribute to the success of a particular method of value creation. Through a series of field interviews, it was determined that the main actors of the green charcoal innovation ecosystem are forest resources governance agencies, biochar producers, boundary organizations, briquette producers, distributors/vendors, the political economy of energy, and the food culture of individuals. The end user (user segment) of this innovation ecosystem is restaurants. Each actor was further analyzed based on the Ecosystem Pie Model methodology as created by Talmar, et al. using the actor’s individual resources, activities, value addition, value capture, dependence on green charcoal and the associated risk as the building blocks for analysis. Based on ecosystem analysis, suggestions were made on how to strengthen the green charcoal innovation ecosystem in Nepal’s renewable energy sector based on actor-actor and actor-green charcoal interactions, associated risks and dependence, and existing knowledge and technology gaps. It was determined that simply deploying a clean cooking technology does not guarantee success of the technology. Rather, there are a multitude of factors that contribute to the success of the clean cooking technology that deserve equal amounts of attention in order to successfully implement the technology.
ContributorsDieu, Megan (Author) / Chhetri, Netra (Thesis director) / Henderson, Mark (Committee member) / Chemical Engineering Program (Contributor, Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05