DISPATCHING AND RELOCATION OF EMERGENCY VEHICLES ON FREEWAYS: THEORIES AND APPLICATIONS

Resource allocation decisions are made to serve the current emergency without knowing which future emergency will be occurring. Different ordered combinations of emergencies result in different performance outcomes. Even though future decisions can be anticipated with scenarios, previous models follow an assumption that events over a time interval are independent. This dissertation follows an assumption that events are interdependent, because speed reduction and rubbernecking due to an initial incident provoke secondary incidents. The misconception that secondary incidents are not common has resulted in overlooking a look-ahead concept. This dissertation is a pioneer in relaxing the structural assumptions of independency during the assignment of emergency vehicles. When an emergency is detected and a request arrives, an appropriate emergency vehicle is immediately dispatched. We provide tools for quantifying impacts based on fundamentals of incident occurrences through identification, prediction, and interpretation of secondary incidents. A proposed online dispatching model minimizes the cost of moving the next emergency unit, while making the response as close to optimal as possible. Using the look-ahead concept, the online model flexibly re-computes the solution, basing future decisions on present requests. We introduce various online dispatching strategies with visualization of the algorithms, and provide insights on their differences in behavior and solution quality. The experimental evidence indicates that the algorithm works well in practice. After having served a designated request, the available and/or remaining vehicles are relocated to a new base for the next emergency. System costs will be excessive if delay regarding dispatching decisions is ignored when relocating response units. This dissertation presents an integrated method with a principle of beginning with a location phase to manage initial incidents and progressing through a dispatching phase to manage the stochastic occurrence of next incidents. Previous studies used the frequency of independent incidents and ignored scenarios in which two incidents occurred within proximal regions and intervals. The proposed analytical model relaxes the structural assumptions of Poisson process (independent increments) and incorporates evolution of primary and secondary incident probabilities over time. The mathematical model overcomes several limiting assumptions of the previous models, such as no waiting-time, returning rule to original depot, and fixed depot. The temporal locations flexible with look-ahead are compared with current practice that locates units in depots based on Poisson theory. A linearization of the formulation is presented and an efficient heuristic algorithm is implemented to deal with a large-scale problem in real-time.

ENGINEERING DIGITAL SHARING PLATFORM TO CREATE SOCIAL CONTAGION: EVIDENCE FROM LARGE SCALE RANDOMIZED FIELD EXPERIMENTS

Peer-to-peer information sharing has fundamentally changed customer decision-making process. Recent developments in information technologies have enabled digital sharing platforms to influence various granular aspects of the information sharing process. Despite the growing importance of digital information sharing, little research has examined the optimal design choices for a platform seeking to maximize returns from information sharing. My dissertation seeks to fill this gap. Specifically, I study novel interventions that can be implemented by the platform at different stages of the information sharing. In collaboration with a leading for-profit platform and a non-profit platform, I conduct three large-scale field experiments to causally identify the impact of these interventions on customers’ sharing behaviors as well as the sharing outcomes. The first essay examines whether and how a firm can enhance social contagion by simply varying the message shared by customers with their friends. Using a large randomized field experiment, I find that i) adding only information about the sender’s purchase status increases the likelihood of recipients’ purchase; ii) adding only information about referral reward increases recipients’ follow-up referrals; and iii) adding information about both the sender’s purchase as well as the referral rewards increases neither the likelihood of purchase nor follow-up referrals. I then discuss the underlying mechanisms. The second essay studies whether and how a firm can design unconditional incentive to engage customers who already reveal willingness to share. I conduct a field experiment to examine the impact of incentive design on sender’s purchase as well as further referral behavior. I find evidence that incentive structure has a significant, but interestingly opposing, impact on both outcomes. The results also provide insights about senders’ motives in sharing. The third essay examines whether and how a non-profit platform can use mobile messaging to leverage recipients’ social ties to encourage blood donation. I design a large field experiment to causally identify the impact of different types of information and incentives on donor’s self-donation and group donation behavior. My results show that non-profits can stimulate group effect and increase blood donation, but only with group reward. Such group reward works by motivating a different donor population. In summary, the findings from the three studies will offer valuable insights for platforms and social enterprises on how to engineer digital platforms to create social contagion. The rich data from randomized experiments and complementary sources (archive and survey) also allows me to test the underlying mechanism at work. In this way, my dissertation provides both managerial implication and theoretical contribution to the phenomenon of peer-to-peer information sharing.

FAMILY CHARACTERISTICS, STATE PROGRAM EFFECTIVENESS, AND REPORT OF INADEQUATE CARE AMONG FAMILIES OF YOUNG CHILDREN WITH HEARING LOSS

Approximately 1.6 per 1,000 newborns in the U.S. are born with hearing loss. Congenital hearing loss poses a risk to their speech, language, cognitive, and social-emotional development. Early detection and intervention can improve outcomes. Every state has an Early Hearing Detection and Intervention program (EHDI) to promote and track screening, audiological assessments and linkage to early intervention. However, a large percentage of children are “lost to system (LTS),” meaning that they did not receive recommended care or that it was not reported. This study used data from the 2009-2010 National Survey of Children with Special Health Care Needs and data from the 2011 EHDI Hearing Screening and Follow-Up Survey to examine how 1) family characteristics; 2) EHDI program effectiveness, as determined by LTS percentages; and 3) the family conditions of education and poverty are related to parental report of inadequate care. The sample comprised 684 children between the ages of 0 and 5 years with hearing loss. The results indicated that living in states with less effective EHDI programs was associated with an increased likelihood of not receiving early intervention services (EIS) and of reporting poor family-centered communication. Sibling classification was associated with both receipt of EIS and report of unmet need. Single mothers were less likely to report increased difficulties accessing care. Poor and less educated families, assessed separately, who lived in states with less effective EHDI programs, were more likely to report non-receipt of EIS and less likely to report unmet need as compared to similar families living in states with more effective programs. Poor families living in states with less effective programs were more likely to report less coordinated care than were poor families living in states with more effective programs. This study supports the conclusion that both family characteristics and the effectiveness of state programs affect quality of care outcomes. It appears that less effective state programs affect disadvantaged families’ service receipt report more than that of advantaged families. These findings are important because they may provide insights into the development of targeted efforts to improve the system of care for children with hearing loss.

Clouds of Suspicion: Airspace Arrangements, Escalation, and Discord in U.S./NATO-Russian Relations

How have cooperative airspace arrangements contributed to cooperation and discord in the Euro-Atlantic region? This study analyzes the role of three sets of airspace arrangements developed by Euro-Atlantic states since the end of the Cold War—(1) cooperative aerial surveillance of military activity, (2) exchange of air situational data, and (3) joint engagement of theater air and missile threats—in political-military relations among neighbors and within the region. These arrangements provide insights into the integration of Central and Eastern European states into Western security institutions, and the current discord that centers on the conflict in Ukraine and Russia’s place in regional security. The study highlights the role of airspace incidents as contributors to conflict escalation and identifies opportunities for transparency- and confidence-building measures to improve U.S./NATO-Russian relations. The study recommends strengthening the Open Skies Treaty in order to facilitate the resolution of conflicts and improve region-wide military transparency. It notes that political-military arrangements for engaging theater air and missile threats created by NATO and Russia over the last twenty years are currently postured in a way that divides the region and inhibits mutual security. In turn, the U.S.-led Regional Airspace Initiatives that facilitated the exchange of air situational data between NATO and then-NATO-aspirants such as Poland and the Baltic states, offer a useful precedent for improving air sovereignty and promoting information sharing to reduce the fear of war among participating states. Thus, projects like NATO’s Air Situational Data Exchange and the NATO-Russia Council Cooperative Airspace Initiative—if extended to the exchange of data about military aircraft—have the potential to buttress deterrence and contribute to conflict prevention. The study concludes that documenting the evolution of airspace arrangements since the end of the Cold War contributes to understanding of the conflicting narratives put forward by Russia, the West, and the states “in-between” with respect to reasons for the current state of regional security. The long-term project of developing a zone of stable peace in the Euro-Atlantic must begin with the difficult task of building inclusive security institutions to accommodate the concerns of all regional actors.

Influence of Nitrogen and Sink Competition on Shoot Growth of Poplar

Terrestrial and oceanic biomass carbon sinks help reduce anthropogenic CO2 emissions and mitigate the long-term effect of increasing atmospheric CO2. Woody plants have large carbon pools because of their long residence time, however N availability can negatively impact tree responses to elevated CO2. Seasonal cycling of internal N in trees is a component that contributes to fitness especially in N limited environments. It involves resorption from senescing leaves of deciduous trees and storage as vegetative storage proteins (VSP) in perennial organs. Populus is a model organism for tree biology that efficiently recycles N. Bark storage proteins (BSP) are the most abundant VSP that serves as seasonal N reserves. Here I show how poplar growth is influenced by N availability and how growth is influenced by shoot competition for stored N reserves. I also provide data that indicates that auxin mediates BSP catabolism during renewed shoot growth. Understanding the components of N accumulation, remobilization and utilization can provide insights leading to increasing N use efficiency (NUE) of perennial plants.

Interorganizational Innovation: The Role of Suppliers in Enhancing Buyer Innovation

This dissertation explores the effect of innovative knowledge transfer across supply chain partners. My research seeks to understand the manner by which a firm is able to benefit from the innovative capabilities of its supply chain partners and utilize the external knowledge they hold to increase its own levels of innovation. Specifically, I make use of patent data as a proxy for firm-level innovation and develop both independent and dependent variables from the data contained within the patent filings. I further examine the means by which key dyadic and portfolio supply chain relationship characteristics moderate the relationship between supplier innovation and buyer innovation. I investigate factors such as the degree of transactional reciprocity between the buyer and supplier, the similarity of the firms’ knowledge bases, and specific chain characteristics (e.g., geographic propinquity) to provide greater understanding of the means by which the transfer of innovative knowledge across firms in a supply chain can be enhanced or inhibited. This dissertation spans three essays to provide insights into the role that supply chain relationships play in affecting a focal firm’s level of innovation. While innovation has been at the core of a wide body of research, very little empirical work exists that considers the role of vertical buyer-supplier relationships on a firm’s ability to develop new and novel innovations. I begin by considering the fundamental unit of analysis within a supply chain, the buyer-supplier dyad. After developing initial insights based on the interactions between singular buyers and suppliers, essay two extends the analysis to consider the full spectrum of a buyer’s supply base by aggregating the individual buyer-supplier dyad level data into firm-supply network level data. Through this broader level of analysis, I am able to examine how the relational characteristics between a buyer firm and its supply base affect its ability to leverage the full portfolio of its suppliers’ innovative knowledge. Finally, in essay three I further extend the analysis to explore the means by which a buyer firm can use its suppliers to enhance its ability to access distant knowledge held by other organizations that the buyer is only connected to indirectly through its suppliers.

Quantifying the Resilience of an Urban Traffic-Electric Power Coupled System

Transportation system resilience has been the subject of several recent studies. To assess the resilience of a transportation network, however, it is essential to model its interactions with and reliance on other lifelines. In this work, a bi-level, mixed-integer, stochastic program is presented for quantifying the resilience of a coupled traffic-power network under a host of potential natural or anthropogenic hazard-impact scenarios. A two-layer network representation is employed that includes details of both systems. Interdependencies between the urban traffic and electric power distribution systems are captured through linking variables and logical constraints. The modeling approach was applied on a case study developed on a portion of the signalized traffic-power distribution system in southern Minneapolis. The results of the case study show the importance of explicitly considering interdependencies between critical infrastructures in transportation resilience estimation. The results also provide insights on lifeline performance from an alternative power perspective.