Browsing by Subject "Technology adoption"
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Item Essays on real options and strategic interactions(2012-08) Dehghani Firouzabadi, Mohammad Hossein; Boyarchenko, Svetlana I.; Almazan, Andres; Stinchcombe, Maxwell B.; Tompaidis, Stathis; Wiseman, ThomasChapter 2 considers technology adoption under both technological and subsidy uncertainties. Uncertainty in subsidies for green technologies is considered as an example. Technological progress is exogenous and modeled as a jump process with a drift. The analytical solution is presented for cases when there is no subsidy uncertainty and when the subsidy changes once. The case when the subsidy follows a time invariant Markov process is analyzed numerically. The results show that improving the innovation process raises the investment thresholds. When technological jumps are small or rare, this improvement reduces the expected time before technology adoption. However, when technological jumps are large or abundant, this improvement may raise this expected time. Chapter 3 studies technology adoption in a duopoly where the unbiased technological change improves production efficiency. Technological progress is exogenous and modeled as a jump process with a drift. There is always a Markov perfect equilibrium in which the firm with more efficient technology never preempts its rival. Also, a class of equilibria may exist that lead to a smaller industry surplus. In these equilibria either of the firms may preempt its rival in a set of technology efficiency values. The first investment does not necessarily happen at the boundary of this set due to the discrete nature of the technology progress. The set shrinks and eventually disappears when the difference between firms’ efficiencies increases. Chapter 4 studies the behavior of two firms after a new investment opportunity arises. Firms either invest immediately or wait until market uncertainty is resolved. Two types of separating equilibrium are possible when sunk costs are private information. In the first type the firm with lower cost invests first. In the second type the firm with higher cost invests first leading to a smaller industry surplus. The results indicate that the second type is possible only for strictly negatively correlated sunk costs. Numerical analysis illustrates that when first mover advantage is large, the firm that delays the investment should be almost certain about its rival’s sunk cost. When market risk increases, the equilibria can exist when the firm is less certain.Item Machina ex deos. Successes and challenges of implementing mobile computing technologies for development. The experience of nine Indian village health projects using a project-issued mobile application(2016-05) Schwartz, Ariel, Ph. D.; Weaver, Catherine, 1971-; Densmore, Melissa; Heinrich, Carolyn; Lentz, Erin; Ward, PeterAs mobile computing technologies become increasingly functional and affordable, global donor and local development organizations find ways to justify and fund their use in grassroots development work. This dissertation asks two questions: (1) In resource-constrained social sector settings, what project features govern and structure use of work-issued mobile devices? And: (2) How do decision-makers adjust to maximize the benefit of newly-introduced devices while minimizing new burdens to the project and project staff? More simply, what variables under social sector projects’ control might promote successful use of information and communication technologies in development (ICTD) projects? This research represents systematic, qualitative comparison of nine extended deployments of a popular mobile health application, CommCare. Each studied project deployed devices loaded with CommCare to health workers in India as a supportive job aid and/or a data collection tool to help monitor beneficiary populations’ health status and frontline workers’ work. This dissertation examines the conditions under which these health workers were able and willing to use CommCare devices in their jobs, and whether and how they deviated from the use of those devices prescribed by their supervisors. Primary data for this study come from 62 in-depth, semi-structured interviews, extensive review of project documents, and personal observations from field study in India over six months in 2013. Employing a sociotechnical lens and a principal agent model, my data support expectations that use of CommCare devices would help align community health workers’ behavior with their supervisors’ organization and mission-related priorities. Use of the devices improved health workers’ professional competence and improved communications, data quality, and data access. These improvements facilitated project supervisors’ monitoring of health workers and beneficiaries, and funders’ monitoring of projects. Contradicting expectations, use of CommCare devices also weakened organizational oversight and control through new data challenges and increased health worker autonomy in their personal and professional lives. These dual benefits and challenges ultimately served the overall projects’ missions.Item Modeling adoption of solar photovoltaics and analysis of net metering in the city of Austin(2011-08) Josyula, Siva Kiran; Rai, Varun; Zarnikau, JaySolar photovoltaics have received government support in the form of rebates, tax credits and net metering tariff mechanisms. The intended goal of these incentives is to encourage innovation in the manufacturing and installation of these systems, which is expected to eventually help overcome the high cost barrier for the adoption of the technology. These systems have the advantages of abundant availability of the solar resource, low environmental footprint, and the possibility of onsite installation, reducing the need for additional generation and transmission capacity. Since millions of dollars have been invested in these incentive programs, there is an interest in tracking the progress in the cost and capacity installed. In the first part of this thesis, I analyzed the trends in costs and adoption of solar PV by residential and commercial customers in the city of Austin. This is accomplished by tabular and graphical analysis of data on PV installations from 2004, when Austin Energy’s rebate program started, to early 2010. In the second part of the thesis, I used technology diffusion models to analyze and forecast the diffusion of residential PV systems in Austin. Three types of models were used to model the adoption trends: Logistic growth model, Bass model without price effects and Bass model including price effects. In the final part of the thesis, I analyzed the net metering tariff mechanism in Austin and studied the difference between the current and an alternative tariff. The alternative tariff uses actual ‘grid usage’ to calculate the energy charge (cost of providing distribution service) instead of the ‘net energy consumed’ that is currently in use. Using simulated PV generation data and ERCOT load profile data, I calculated the difference in revenue for Austin Energy with the alternative tariff. The results indicate that the alternative tariff adds little revenue to Austin Energy’s energy charge revenues at the current level of penetration of solar PV. However, at a higher penetration level of PV, the alternative tariffs might result in significant additional revenue for the utility. The thesis concludes with a discussion on the possible rationale for the alternative tariff and directions for future research.Item Multidisciplinary thinking to increase sustainability in engineering : a case study in sanitation(2016-05) Wood, Alison P.; Lawler, Desmond F.; Blackhurst, Michael F.; McKinney, Daene C.; Kirisits, Mary Jo; Olmstead, Sheila M.This dissertation uses a case study in sanitation that illustrates the need for interdisciplinary analysis of sustainable solutions to engineering problems. This case study also suggests that one nontechnical factor that might be critical for increasing sustainability is consumer willingness to use the technology, which, along with factors such as cost, will drive technology adoption rates. By developing the ability and willingness to recognize needs for this type of interdisciplinary work and by collaborating with experts in other fields, engineers can more successfully create sustainable solutions to the problems they tackle. The work of this dissertation is in three stages. The first comprises a life cycle cost and cost-effectiveness analysis for a suite of household sanitation technologies. Results of this stage suggest that decentralized technologies are lower cost and more cost-effective for nitrogen management than conventional centralized wastewater treatment in the given case study location; composting and urine-diversion toilets proved the best performers on these metrics. The second stage of research expands the analysis to examine adoption of decentralized sanitation technologies as a two-party decision, with the individual discount rate used as a proxy for factors influencing homeowners’ adoption decisions. Results in two case study locations emphasize the dependence of analysis on case-specific details; in one case, monetary incentives are expected to be successful at bringing municipal and individual decision-makers into agreement to adopt decentralized sanitation systems under many cost scenarios, while monetary incentives are not expected to succeed at bringing about agreement between parties in the other case. The third stage of research uses a survey to examine non-monetary factors influencing homeowners’ adoption decisions surrounding composting and urine-diversion toilets. Results suggest that educational efforts are likely to be important in influencing adoption decisions, although not all homeowners will be swayed by additional information. Together, the three stages of this research illustrate how understanding of technologies as potential solutions to problems of sustainability changes as the analysis expands to incorporate methods from more disciplines. While true assessment of “sustainability” is difficult at best, movement toward increasingly sustainable technologies can be facilitated by broader analyses that lead to more thorough understanding.Item The rationalities behind the adoption of cyberinfrastructure for e-science in the early 21st century U.S.A.(2010-08) Kee, Kerk Fong; Browning, Larry D.; Ballard, Dawna I.; Boisseau, John R.; Rice, Ronald E.; Stephens, Keri K.Based on grounded theory and thematic analysis of 70 in-depth interviews conducted over 32 months (from November 2007 to June 2010) with domain scientists, computational technologists, supercomputer center administrators, program officers at the National Science Foundation, social scientists, policy analysts, and industry experts, this dissertation explores the rationalities behind initial adoption of cyberinfrastructure for e-science in the early 21st century U.S. This dissertation begins with Research Question 1 (i.e., how does cyberinfrastructure's nature influence its adoption process in early 21st century U.S.?) and identifying four areas of challenging conditions to reveal a lack of trialability/observability (due to the participatory/bespoke nature), a lack of simplicity (due to the meta/complex characteristic), a lack of perceived compatibility (due to the disruptive/revolutionary quality), and a lack of full control (due to the community/network property). Then analysis for Research Question 2 (i.e., what are the rationalities that drive cyberinfrastructure adoption in early 21st century U.S.?) suggests that there are three primary driving rationalities behind adoption. First, the adoption of cyberinfrastructure as a meta-platform of interrelated technologies is driven by the perceived need for computational power, massive storage, multi-scale integration, and distributed collaboration. Second, the adoption of cyberinfrastructure as an organizational/behavioral practice is driven by its relative advantages to produce quantitative and/or qualitative benefits that increase the possibility of major publications and scientific reputations. Third, the adoption of cyberinfrastructure as a new approach to science is driven and maintained by shared visions held by scientists, technologists, professional networks, and scientific communities. Findings suggests that initial adoption by pioneering users was driven by the logic of quantitative and qualitative benefits derived from optimizing cyberinfrastructure resources to enable breakthrough science and the vision of what is possible for the entire scientific community. The logic was sufficient to drive initial adoption despite the challenging conditions that reveal the socio-technical barriers and risky time-investment. Findings also suggest that rationalization is a structuration process, which is sustained by micro individual actions and governed by macro community norms simultaneously. Based on Browning’s (1992) framework of organizational communication, I argue that cyberinfrastructure adoption in the early 21st century lies at the intersection of technical rationalities (i.e., perceived needs, relative advantages, and shared visions) and narrative rationalities (i.e., trialability, observability/communicability, simplicity, perceived compatibility, and full control).Item Three Essays on the Economics of Precision Agriculture in Cotton Production(2011-05) Nair, Shyam; Wang, Chenggang; Maas, Stephan J.; Segarra, Eduardo; Knight, Thomas; Johnson, JeffPrecision agriculture technologies aim at adjusting input application rates to spatial and temporal requirements of the crop increasing the input use efficiency and reducing the negative environmental impact associated with agricultural chemicals. Two most important aspects of precision agriculture in cotton are development of precision agriculture technologies and dissemination of the developed technologies to the end users. The three essays in this dissertation address both of these issues by analyzing a survey of the status of precision agriculture adoption by cotton farmers in 12 states of Southern US and developing cotton irrigation strategies optimizing temporal and spatial allocation of limited water supply. In the first essay, a nested logit model was used to analyze the adoption of different variability detection technologies and the likelihood of adoption of the variable rate application conditioned on the type of variability detection technology chosen by the decision maker. The results revealed that the farmers choosing more than two variability detection technologies are more likely to adopt variable rate application technology. In the second essay a biological model was used along with an economic optimization model to determine the optimal strategy for temporal allocation of irrigation water at different levels of available irrigation water (6, 9, 12, and 15 acre-inch). From this study, it was evident that irrigating only 30%, 45%, 55%, and 70% of the field and keeping the rest of the field rainfed was the best strategy to maximize the profit under 6, 9, 12, and 15 inches of available irrigation water, respectively. The third study examined different strategies to allocate a limited amount of irrigation water among three stages of cotton growth. At 15 inches of available irrigation water, the strategy that maximizes risk adjusted profit was to use 90% of the available irrigation water from first bloom to first open boll and the rest from appearance of the first open boll to 60% open boll. At all other levels of available irrigation water, the best strategy was to apply all the available irrigation water from appearance of first bloom to appearance of first open boll.