Abstract: The COVID-19 pandemic, which was declared by the World Health Organization on March 11, 2020, negatively impacted virtually all economic and social activities across the globe. As of March 7, 2022, more than 6 million deaths have been associated with COVID-19 disease. This health disaster, unlike many other disasters, is not limited to time or location. It has resulted in intense global competition for many essential products, from Personal Protective Equipment (PPE) to ventilators and vaccines and food products. In this dissertation, I construct, analyze, and quantitatively solve a spectrum of supply chain economic network models inspired by realities in the COVID-19 pandemic in four essays.

In this dissertation, I first develop a game theory network model for integrating financial and logistical challenges that humanitarian organizations involved in disaster management are faced with. This part of the dissertation illustrates how game theory can be utilized in the modeling and analysis of the behavior of multiple decision-makers that interact with each other in disaster supply chain economic networks under different constraints.

I, subsequently, construct the first Generalized Nash Equilibrium (GNE) model with stochastic demands to model competition among organizations at demand points for medical supplies inspired by the COVID-19 pandemic. The theoretical constructs are provided, and a Variational Equilibrium is utilized to enable alternative variational inequality formulations. Then, I delve more deeply into an important characteristic of disasters, that of uncertainty, by developing a two-stage stochastic game theory network model. Specifically, the first multistage stochastic GNE model is constructed for the study of competition among multiple countries for limited supplies of medical items in the disaster preparedness and response phases in the COVID-19 pandemic. Illustrative examples and algorithmically solved numerical examples, inspired by the need for N95 masks and ventilators, are presented.

Finally, I turn to a key aspect of pandemic disaster management, which is the evaluation of trade instruments that governments have been applying during the pandemic to protect their citizens. Specifically, a unified variational inequality framework in the context of spatial price network equilibrium problems is constructed that focuses on a plethora of essential products, that are in high demand in the pandemic, but short in supply globally. The model allows one to seamlessly introduce various trade measures, including tariffs, quotas, as well as price floors and ceilings.

Abstract: In this dissertation, I focus on the modeling and analysis of some of the inherent issues in competitive perishable food supply chain networks. I investigate the impacts of trade policies such as tariffs, quotas, and their combination – tariff-rate quotas, as well as the integration of food quality deterioration into food supply chains. The research is especially timely given the prevalence of trade wars and tariffs in today’s global political environment. The work is multidisciplinary with constructs from food science integrated into the economics of supply chain networks.

The first part of the dissertation overviews the methodological foundations including game theory, network and optimization theory, and variational inequality theory used for the construction and solution of the supply chain network models. In the second part of the dissertation, I first focus on perfectly competitive problems and develop a unified variational inequality framework for spatial price network equilibrium problems with tariff-rate quotas. The accompanying case study on the dairy industry is based on trade between the United States and France. The computational results reveal that tariff-rate quotas may protect domestic producers from foreign competition, but at the expense of higher demand prices for consumers. This work is based on the paper by Nagurney, Besik, and Dong (2019). I then develop an oligopolistic supply chain network equilibrium model with differentiated products consisting of multiple firms, production sites, and demand markets, in which firms compete on product quantities and also quality. I provide a case study on soybeans, an important agricultural product, and investigate different scenarios. Insights as to firm profits and trade volumes, the average product quality, and consumer welfare, are also delineated. Specifically, I find that, although firms may benefit from the imposition of a quota or tariff, the welfare of consumers in the country imposing the quota or tariff declines. This work is based on the paper by Nagurney, Besik, and Li (2019).

In the third part of my dissertation, I demonstrate how to incorporate quality deterioration of fresh produce into perishable supply chain network models. I construct an explicit equation for fresh produce quality deterioration based on time and temperature of different pathways in supply chain networks. I first incorporate this feature into local markets in the form of farmers markets, which serve as examples of direct to consumer channels and shorter supply chain networks. I also provide a case study of apples in western Massachusetts, under various scenarios, including production disruptions, due to negative weather conditions, resulting in an increase in apple prices at farmers markets, a decrease in quality, and a decrease in profits for the apple orchards. These results can be used to inform food firms, policy makers, and regulators. This work is based on the paper by Besik and Nagurney (2017). Subsequently, I develop a competitive food supply chain network model in which the profitmaximizing producers decide not only as to the volume of fresh produce, but they also decide on the initial quality of fresh produce, with associated costs. I incorporate quality deterioration of the fresh produce explicitly with chemical functions depending on time, temperature, and the initial quality of the food product. I then present a case study on peaches, with supply chain disruptions to reveal valuable insights. I find that the disruptions in production result in higher demand prices, and lower initial quality. This is the first such general supply chain network model constructed to include the initial quality of fresh produce. This part of the dissertation is based on the paper by Nagurney, Besik, and Yu (2018).

Abstract: A crucial component of every healthcare system is the safe and steady supply of the life-saving product, blood. In order to meet the demand for blood consistently, it is imperative to maintain a robust supply chain. The blood banking industry in the United States, faced with emerging challenges, which include, but are not limited to, an increase in operating costs, rise in competition among blood centers, insufficient reimbursement from payers such as insurance companies and government programs, in addition to inherent challenges such as donor motivation, seasonal shortages, perishability, is trying to adapt to the changing dynamics to sustain itself economically.

The nonprofit nature of this industry and thefinancial implications for its various stakeholders, makes the efficient management of blood supply chains an important and interesting area of study.

In this dissertation, I contribute to the existing literature on blood banking by modeling the operational and economic challenges throughout the blood supply chain in the context of competition using game theory. I develop a model for blood service organizations competing for donations where they use service quality levels at collection sites as their strategic variables to increase their collection of whole blood from voluntary donors. I further construct a competitive blood supply chain network model that captures all major activities as well as perishability along the supply chain from collection of blood to distribution to hospitals.

As a crucial extension to the study on blood supply chains, I develop a network framework with multiple tiers of decision-makers including payers, that captures the decentralized nature of the blood banking system in the United States. The solutions from this multi-objective decision making problem include quantities of blood to be supplied and transfused, given demand is known, as well as the financial transactions between the different tiers of stakeholders. For each model the governing equilibrium conditions are derived, and equivalent variational inequality formulations presented. The models and their relevance are further illustrated through simulated case studies focusing on different parts of the United States. The results obtained provide valuable insights that can inform healthcare policy makers and regulators.

Abstract: In a constantly and intricately connected world that is going digital, cybersecurity is imperative to not just the success but also the survival of a business. The ubiquitous digital transformation is fueled by a convulsive growth of devices and data that are leading important innovations in the domain of cyber-physical systems. However, this growth has also enabled internal and external threats to skyrocket, depicting the inherent dichotomy. With an evolving threat landscape, a perpetrator has to be successful once, while the defenders have to continually succeed in fending-off attacks to protect critical infrastructure and digital assets.

The retail and financial sectors are prime targets owing to the large amounts of personal and financial information they process in disperse and distributed environments. One of the biggest retail breaches was that of Target when 30 million credit card numbers and personal information of 70 million customers were stolen and sold on the dark net (Riley and Pagliery (2015)). In the financial sector, JP Morgan Chase lost data of 83 million customers. The accused laudered the $100 million obtained, used 75 shell companies that employed hundreds of people, and 30 fake passports from 17 countries to keep the money hidden (Pagliery (2015)).

Monetization of this sensitive data validates that the motivation of such criminals is principally financial. According to NTT 2016 Global Threat Intelligence Report, retailers are experiencing nearly three times as many cyberattacks as those by financial service providers that were top targets until 2014. Thus, in this dissertation, the focus is, mainly, on the retail and financial sectors, the top two sufferers in the recent past.

Increased sophistication in cyber threats can be attributed to the fact that criminals are now highly skilled, well-funded, coordinated, and organized. As a result, worldwide security breaches are increasing at just about 40% per annum and attackers stay undetected for an average of 200 days. One of the prominent examples of slow detection is the negligence suit led by Yahoo users over a 2014 breach that compromised personal data of 500 million users but was discovered recently in 2016 (Vishwanath (2016)). While large organizations are cautious (JPMorgan doubled its cybersecurity spending to $500 million in 2015; Global information security spending will increase by 36% to $101 billion by 2018 (Purnell (2015))), the small and medium level enterprises are not known for ensuring basic precautionary measures (Forrester (2016)), which stems from their belief that attacks on larger organizations are more consequential. Unfortunately, cyber criminals do not discriminate.

Businesses are facing a barrage of attacks, majority of which have a financial or an espionage motive. In a highly interconnected and mutually dependent world, organizations are constantly interacting and transacting with each other. If one organization in this complex network is breached, there could be ramfications for the others since they might also be vulnerable. Often, attackers circumvent sophistical organizational rewalls and go after soft targets (CNN (2016)). Against the hackers, businesses put forth an asymmetric and myopic struggle.

Organizing funds for proactive and targeted responses requires careful security investment decision-making. In view of the above, a network approach to security investments while evaluating vulnerabilities of the individual organizations and the entire network is essential. Cyber threat cannot be eliminated, rather the culminating risks need to be managed. Investments in stronger defense mechanisms, preventive protocols, cyber intelligence, and agile systems that provide required redundancies or backups could aid in effective risk management.

If threats are rampant in the cyber space, physical supply chain networks are also not exempt from thefts, losses, and damages. In 2015, 1500 incidents of cargo theft, heavy commercial vehicle theft, and identity theft of trucking companies in the United States and Canada was reported. Out of these, in about 470 thefts, cargo and assets worth $98 million were stolen. The average theft loss value per incident was $187,490 (CargoNet(2015)). Some of the principal choke points that attackers manipulate are poor infrastructure and transportation networks, lax port security, and inadequate telecommunications to support tracking devices. Threats can vary by product type, mode of transportation, freight carriers, region, and even day of the week.

In view of the above, this work attempts to answer the following principal questions: (i) For competing firms in a network, what should their security levels be considering their investment costs or budget constraints to ensure a reduction in the entire network's vulnerability? (ii) If firms in a network cooperate, what are the implications on the network vulnerability? Does cooperation yield more economic/financial benefits? (iii) In a supply chain network for high value cargo with competing freight service providers, what should the shipment sizes and security levels be to ensure reduction in vulnerability?

Through this dissertation, I contribute to the modeling and analysis of security investments in cyber and sup- ply chain networks considering network vulnerability also nonlinear budget constraints. The latter contributes significantly to the literature on variational inequality, game theory, and cybersecurity by being methodologically relevant to the application and solution of such problems. I also explore cooperation in terms of cybersecurity among firms in a network, providing a quantitative basis to information sharing to explore its financial and policy related benets. This work extends the current literature in the cooperative game theory and cybersecurity domains. In addition, I explore the high value cargo supply chains that are faced with security investment decisions at the freight service providers' level. All the models presented in this dissertation are neither limited to a fixed number of firms or customers, nor to functions of any specific form. Moreover, very few cybersecurity or supply chain security investment models using game theory with competition, network perspective, network vulnerability, nonlinear budget constraints, and cooperation have been solved to-date.

The first part of this dissertation discusses the introduction of and motivation behind this research endeavor, along with a detailed literature review. Next, I discuss the contributions of the work I have undertaken. An overview of relevant methodologies, including variational inequality theory, competitive game theory, cooperative game theory and Nash bargaining theory, and two algorithms used in the chapters to follow is also provided.

Subsequently, I present a supply chain network model in which firms compete on security levels and product flows. The study takes a network approach to cybersecurity investment decision-making to obtain Nash equilibrium and ascertain vulnerabilities of the individual rms and the network on the whole. The model is probabilistic and includes demand side of the network along with its dynamics.

In the next part, a crucial and unique extension to the cybersecurity investment and risk determination model as discussed in the previous part is considered. Nonlinear budget constraints are added to the model that increase its complexity and call for theoretical and methodological contributions.

Thereafter, the cybersecurity investment model is modified to include a cooperative game approach to address the pressing need of collaboration and information sharing among firms in a network through which they can present a more coordinated front against the emerging cyber threat landscape. This inclusion is pivotal to the cybersecurity investment decisions.

Finally, I include my work that advanced modeling of physical security in supply chain networks. My current work in cybersecurity competition and cooperation was leveraged to cater to security investments regarding cargo, infrastructure, and other assets. The model contains features that are innate to physical ows and networks, thereby, marking a distinction from my work in cybersecurity. It deals, primarily, with security investment decisions in the presence of competing freight service providers shipping high value cargo from shipping origins to demand market destination points.

The dissertation is based on the following papers: Nagurney, Nagurney, and Shukla (2015), Nagurney, Daniele, and Shukla (2017), Nagurney and Shukla (2017), and Nagurney, Shukla, Nagurney, Saberi (2017).

Abstract: The Internet has transformed the way in which we conduct business and perform economic and financial transactions, communicate and obtain information, and even experience music and entertainment. Customers’ demands, however, are driving the Internet and telecommunication networks towards providing quality-based services. One key challenge in the Internet is the inefficiency of the mechanisms by which technology is deployed and the business and economic models surrounding these processes (Wolf et al. (2014)). Equilibrium models for the Internet generally assume basic economic relationships. However, in new paradigms for the Internet and even in the case of supply chain networks, price is not the only factor but quality of service (QoS) is of increasing importance (Nagurney, Li, Wolf, and Saberi (2013)). The economic complexity associated with designing the future Internet with differentiated services is further advancing the role of pricing models (Jain, Durresi, and Paul (2011)).

Supply chains networks, which give us the means to manufacture the products and deliver them to points of demand across the globe, are also under many pressures to offer differentiated products and services (Nagurney (2014)). It is well-known today that success is determined by how well the entire supply chain performs, rather than the performance of its individual entities. Quality has become one of the most essential factors in the success of supply chain networks (Floden, Barthel, and Sorkina (2010)). However, in todays’ multimodal distribution networks with intense competition among freight service providers, the integration of price and quality competitive behavior has not been examined in a rigorous theoretical and computationally tractable framework.

In this dissertation, I contribute to the analysis, design, and management of the future Internet and supply chain networks with a focus on price and quality competition in serviceoriented networks. This dissertation begins with an introduction, the research motivation for, and a review of the relevant literature, followed by the theoretical foundations of the mathematical framework employed including optimization theory, variational inequality (VI) theory, and projected dynamical systems theory.

In the second part of this dissertation, I focus on economic models for the future Internet. Generally, providers in the Internet face many challenges in determining technical and economic solutions in offering services with different QoS (Wolf et al. (2012)). Key challenges are how to find the equilibrium prices and quality levels in an oligopoly market of service providers in a service-oriented Internet which provides quality-based services. In order to answer this question, I develop both a basic and a general network economic game theory model of a quality-based service-oriented Internet to study the competition among the service providers (both content and network ones) in Chapter 3. I also analyze the effects of the prices that the network providers charge the content providers for data transmission in the basic model.

Moreover, it is imperative to study and analyze the underlying dynamics of the various economic decision-makers involved from content providers to transport network service providers in terms of both pricing as well as quality. In this case, novel insights into the networks’ structures can be obtained by taking into account the associated economic models and equilibrium conditions among providers (Nagurney, Li, Wolf, and Saberi (2013)). In Chapter 4, I, then, develop a dynamic network economic model of a service-oriented Internet with price and quality competition using projected dynamical systems theory. For this model, consumers respond at the demand markets through the demand functions which reflect the attractiveness of the composition of content and network services as reflected by the prices charged and the quality levels.

The pricing of Internet services merely based on quality and data usage, as is now typical, with contracts of one to two years duration can lead to network congestion since network resource utilization may change over time. Furthermore, consumers may desire greater flexibility and more choices. Hence, it is expected that contract duration will become an important feature in the pricing of network services (Hwang and Weiss (2000)). To assess the prices for various contract durations at the demand markets as well as the levels of quality, an economic analysis through a rigorous game theory framework is essential. My approach in Chapter 5 to resolve this void is a game theory model of a service-oriented Internet in which the network providers compete in usage service rates, quality levels, and duration-based contracts, to find the effect of quality and the duration of Internet network contracts on the Internet service pricing.

Furthermore, the growth of intercontinental multi-channel distribution networks has led to fierce competition among freight service providers who are subjected to pricing pressures and increased expectations to handle more complex services (Hakim (2014) and DHL (2014)). In the third part of this dissertation (Chapter 6), I construct a model that captures the competition among manufacturers and freight service providers in a supply chain network. This model is the first one in the literature that handles both price and quality competition with multiple modes of shipment from both equilibrium and dynamic perspectives. The manufacturers compete with one another in terms of price and quality of the product manufactured, whereas the freight service providers compete on price and quality of the transportation service they provide for multiple modes. Both manufacturers and freight service providers maximize their utilities (profits) while considering the consequences of the competitors’ prices and quality levels. Limits on prices and quality levels are included that have relevant policy-related implications.

For each model, I derive the governing equilibrium conditions and provide the equivalent variational inequality formulations. The models presented here are accompanied by a detailed qualitative analysis that provides conditions for existence and uniqueness of equilibrium patterns. In order to illustrate the modeling framework and the algorithm, I present computed solutions to several numerical examples for each model as well as sensitivity analysis results.

This dissertation is heavily based on the following papers: Saberi, Nagurney, and Wolf (2014), Nagurney, Li, Saberi, and Wolf (2014), Nagurney, Saberi, Wolf, and Nagurney (2015), and Nagurney, Saberi, Shukla, and Floden (2015) as well as additional results and conclusions.

This research was supported, in part, by the National Science Foundation (NSF) grant CISE #1111276, for the NeTS: Large: Collaborative Research: Network Innovation Through ChoiceNet project awarded to the University of Massachusetts Amherst. This support is gratefully acknowledged.

Abstract: The quality of the products produced and delivered in supply chain networks is essential for consumers' safety, well-being, and benefits, and for firms' profitability and reputation. However, because of the complexity of today's large-scale highly globalized supply chain networks, along with issues such as the growth in outsourcing and in global procurement, as well as the information asymmetry associated with quality, supply chain networks are more exposed to both domestic and international quality failures.

In this dissertation, I contribute to the equilibrium and dynamic modeling and analysis of quality competition in supply chain networks under scenarios of information asymmetry, product differentiation, outsourcing, and under supplier selection.

The first part of the dissertation consists of a review of the relevant literature, the research motivation, and an overview of methodologies.

The second part of the dissertation formulates quality competition with minimum quality standards under the scenario of information asymmetry, specifically, when there is no product differentiation by brands or labels.

In the third part, in contrast, quality competition is modeled under product differentiation, when firms engage in distinguishing their products from their competitors'.

The fourth part concentrates on quality competition in supply chain networks with outsourcing. The models yield the optimal make-or-buy and contractor selection decisions for the firm(s) and the optimal pricing and quality decisions for the contractors. The impacts of firms' attitudes towards disrepute are also studied numerically.

In the fifth part, a multitiered supply chain network model of quality competition with suppliers is developed. It consists of competing suppliers and competing firms who purchase components for the assembly of their products and, if capacity permits, produce their own components. The optimal supplierselection decisions, optimal component production and quality, and the optimal quality preservation levels of the assembly processes are provided. Such issues as the values of the suppliers to the firms, the impacts of capacity disruptions, and the potential investments in capacity enhancements are explored numerically.

The models and analysis in this dissertation can be applied to numerous industries, ranging from the food industry to the pharmaceutical industry, automobile industry, and to the high technology industry.

Abstract: Supply chains for time-sensitive products, and, in particular, for perishable products, pose specific and unique challenges. By denition, a perishable product has a limited lifetime during which it can be used, after which it should be discarded (Federgruen, Prastacos, and Zipkin (1986)).

In this dissertation, I contribute to the analysis, design, and management of supply chain networks for perishable products with applications to healthcare. Specifically, I construct generalized network frameworks to capture perishable product supply chains in healthcare operating under either centralized or decentralized decision-making behavior. The dissertation is motivated by applications ranging from blood supply chains to pharmaceuticals, such as vaccines and medicines. The novelty of the modeling and computational framework includes the use of arc mul tipliers to capture the perishability of the healthcare product(s), along with waste
management costs, and risk.

The first part of the dissertation consists of a literature review of perishable product supply chains with a focus on healthcare along with an overview of the relevant methodologies.

The second part of the dissertation formulates supply chains in healthcare operating under centralized decision-making behavior. In this part, I focus on both the operations management of and the sustainable design of blood supply chains and construct models for regionalized blood banking systems as belonging to the Red Cross.

The third part of the dissertation considers competitive behavior, with a focus on the pharmaceutical industry. I construct an oligopoly supply chain network model, with differentiated brands to capture the competition among producers of substitutable drugs using game theory and variational inequality theory. Furthermore, using a case study based on real-world scenarios of a highly popular cholesterol-reducing branded drug, the impact of patent rights expiration of that brand is explored which coincides the time when its equivalent generic emerges into the markets. The calculated results are then compared to the observations from the real-word problem.

Finally, the projected dynamical system formulation of the pharmaceutical network oligopoly model is derived.

This dissertation is based on the following papers: Nagurney, Masoumi, and Yu (2012), Nagurney and Masoumi (2012), and Masoumi, Yu, and Nagurney (2012) as well as additional results and conclusions.

Abstract: With supply chains spanning the globe, and with increasing time-sensitivity for various products in many markets, timely deliveries are becoming a strategy, as important as productivity, quality, and even innovation (see, e.g., Gunasekaran, Patel, and McGaughey (2004), Christopher (2005), and Nagurney (2006)).

A product is considered to be time-sensitive, if there is a strict time requirement regarding that product, either as a characteristic of the product itself or on the demand side. In particular, a time-sensitive product must have at least one of the following two properties:

• the product loses its value rapidly, due to either obsolescence or perishability, which can lead to extra waste and cost, if unused;
• the demand for it is sensitive to the elapsed time for the order fulllment; the failure to satisfy the demand on-time may result in the loss of potential market share, or, even worse, additional injuries or death as in times of crises.

This dissertation formulates, analyzes, and solves a spectrum of supply chain network problems for time-sensitive products, ranging from fast fashion to food to pharmaceuticals. Specifically, I first develop a model that captures the trade-offs between the operational costs and time issues in the apparel industry. I then construct a sustainable fashion supply chain network model under oligopolistic competition and brand differentiation. I, subsequently, capture the deterioration of fresh produce along the entire supply chain through arc mul- tipliers with time decay. Finally, I consider the supply chain network design problem for critical needs products, as in times of crises and humanitarian relief operations. I also develop a supply chain network design/redesign model with multiple products, with particular relevance to healthcare.

This dissertation consists of advances in the modeling, analysis, and design of supply chain networks for time-sensitive products, all unied through the methodology of varia- tional inequality theory (see Nagurney (1999)), coupled with network theory and multicri- teria decision-making. The framework captures the underlying behavior associated with the operation and management of the associated supply chains, whether that of central optimization or competition, allows for the graphical depiction of the supply chain network structures, and efficient and effective solution.

Abstract: It is believed that the critical next step from examinations of operations and the environment is the study of sustainability nd supply chains (Linton, Klassen, and Jayaraman (2007)). Environmental quality and preservation as well as meeting the stress of emission reductions is rapidly becoming an important isue for public policy (Wilkinson, Hill, and Gollan (2001)). However, Lambertini and Mantovani (2007) note the disregard, unrelated to regulatory requirements, of research practitioners to the potential benefits of appropriate competition policy measures and consumer pressures (Srivastara (2007)). In addition, a firm's success, notably, in terms of financial and/or environmental practices, has been tied, in part, to the strength of its ability to coordinate and integrate activities along the entire supply chain (Spekman, Kamauff Jr., and Myhr (1998)), and to effectively implement multicriteria decision-making tools to aid in their strategic decisions.

I present five essays in this dissertation. For each model I utilize the theory of variational inequalities, derive the formulation, present qualitative properties, and provide numerical examples. The first essay develops the multitiered sustainable supply chain network model with multicriteria decision-making. In the second essay I construct a modeling and computational framework that allows for the determination of optimal carbon taes applied to electric power plants in the context of electric power supply chain generation / distribution/ consumption) networks. The third essay considers electric power supply chain networks and develops a model of tradable pollution permits in the case of multiple pollutants and spatially distinct receptor points. In the fourth essay, I quantify and assess, from a system-optimized sustainable supply chain network perspective, the environmental effects resulting when a horizontal supply chain integration occurs. In the fifth and final essay, I extend the work of Nagurney (2009) to the multiproduct supply chain network domain to quantify the impacts.

This dissertation is heavily based on the following papers: Nagurney, Liu, and Woolley (2006), Nagurney, Liu, and Woolley (2007), Woolley, Nagurney, and Stranlund (2009), Nagurney and Woolley (2009) and Nagurney, Woolley, and Qiang (2009).

Abstract: The recent theories of scale-free and small-world networks have significantly enhanced our understanding of the behavior as well as the vulnerability of many real-world networks. However, the majority of network vulnerability studies focus solely on the topological characteristics. Although the topological structure of a network provides crucial information regarding network vulnerability, the flow on a network is also an important indicator, as are the flow-induced costs and the behavior of the users.

Latora and Marchiori (2001, 2002, 2004) proposed a network efficiency measure that is shown to have advantages over several existing network measures. Nevertheless, their measure only considers geodesic information and, therefore, ignores important factors such as flows, costs, and behaviors.

The first objective of this dissertation is to construct a network efficiency/performance measure that extends the Latora-Marchiori measure to incorporate such important network factors as flows, costs, and behaviors in order to assess the importance of network components. It is shown that the new network measure has advantages over several existing network measures. Furthermore, the measure is able to handle both fixed and elastic demands as well as static and dynamic networks, with the latter of particular relevance to the Internet. Moreover, it enables a ranking of the importance of network components.

In addition, instead of looking at the situation where a network component is completely disrupted, network robustness, another important aspect of the network vulnerability, investigates cases in which network resources are reduced in stressful environments. The second goal of this dissertation is to study transportation network robustness based on the new network efficiency/performance measure in order to investigate the network functionality when the links are partially degraded. I also evaluate transportation network robustness under different user behaviors and with environmental concerns.

Furthermore, based on the recent results regarding the supernetwork equivalence between transportation networks and supply chain networks as well as financial networks (Nagurney (2006a) and Liu and Nagurney (2007)), I apply the new network measure to study multitiered financial networks with intermediation. I also propose a novel supply chain model with disruption risks and uncertain demands and define a weighted supply chain network performance measure.