A new vision of Trans-Eurasian transportation

By Katherine Leitzell, IIASA Science Writer and Press Officer

The Trans-Siberian Railway is the longest railway in the world, connecting Moscow with Vladivostok and the Sea of Japan. Built at the turn of the 19th century, the railroad network connected remote Eastern Russia with the rest of the country, and created the first overland link between Europe and Asia.

In a meeting last week at IIASA, Russian researcher Yury Gromyko presented an equally ambitious transportation “megaproject” for the next century: the Trans-Eurasian Belt of Razvitie (Development in Russian), or the TEBR. The project, led by a group of leading Russian intellectual centers, would provide a new transportation network between markets in Europe and Asia, including high-speed rail, roads, as well as infrastructure such as pipelines and telecommunications networks.

Maglev trains, like this one in Shanghai, would be one component of the envisioned TeBR project. © 06photo | Dreamstime.com

Maglev trains, like this one in Shanghai, would be one component of the envisioned TEBR project. © 06photo | Dreamstime.com

Yet in Gromyko’s view the TEBR is also a development project that would bring new opportunities for trade and employment to the entire corridor of the construction. Gromyko described the project as a “New Future Zone,” which could revolutionize trade and economic development across Eurasia.

If the TEBR succeeds, Gromyko envisions new networks of smart cities in eastern Russia based on innovative technologies and new industries that would stem the tide of migration towards Moscow, instead pulling a new generation eastwards. “We need millions of young people to move to the Russian Far East. To attract them, there would need to be exciting jobs and affordable housing,” said Gromyko.

Gromyko presented the project at a workshop entitled, Development of Transport and Infrastructure in Eurasia. The meeting brought together transportation experts from across Eurasia to discuss visions for future development of the continent, and the key role of a multi-infrastructure approach in that development. Multi-infrastructure presupposes integration of different infrastructures from transportation to energy and telecommunications.

“Transportation and infrastructure are simply integral to economic development,” explains Michael Emerson, a senior researcher in the project who splits his time between the Centre for European Policy Studies (CEPS) and IIASA. “You cannot have one without the other.”

Credit: Russian Academy of Sciences

Credit: Russian Academy of Sciences

The event was the 5th in a series of scoping workshops arranged as part of the IIASA-coordinated project, Challenges and Opportunities of Economic Integration within a wider European and Eurasian Space, following previous workshops focused on research methodology, trade policy, non-tariff barriers, and energy. In addition to transportation and infrastructure projects, participants discussed investment and finance options for such major international efforts, as well as the challenges and opportunities of drawing private investment for long-term investments in infrastructure.

Several more scoping workshops are planned on different dimensions related to economic regional integration, explained project leader Elena Rovenskaya, the director of IIASA’s Advanced Systems Analysis Program. They create the foundation for the research phase involving researchers, business leaders, and policymakers from across Eurasia.

More information
Project: Challenges and Opportunities of Economic Integration within a Wider European and Eurasian Space 

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Network science and marketing: A virus’ tale

By Matthias Wildemeersch,  IIASA Advanced Systems Analysis and Ecosystems Services and Management Programs

FotoQuest Austria is a citizen science campaign initiated by the IIASA Ecosystems Services & Management Program that aims to involve the general public in mapping land use in Austria. Understanding the evolution of urban sprawl is important to estimate the risk of flooding, while the preservation of wetlands has important implications for climate change.

But how can we engage people in environmental monitoring, in particular when they are growing increasingly resistant to traditional forms of advertising? Viral marketing makes use of social networks to spread messages, and takes advantage of the trust that we have in the recommendation coming from a friend rather than from a stranger or a company.

Network science and the formal description of spreading phenomena can shed light on the propagation of messages through communities and can be applied to inform and design viral marketing campaigns.

Viral spreading © kittitee550 | Dollar Photo Club

Viral spreading © kittitee550 | Dollar Photo Club

Network science is a multi-disciplinary field of research that draws on graph theory, statistical mechanics, inference, and other theories to study the behavior of agents in various networks. The spreading phenomena in viral marketing show similarities with well-studied spreading processes over biological, social, physical, and financial networks. For instance, we can think about epidemics,which are well understood and allow for the design of optimal strategies to contain viruses. Another example is opinion dynamics, which received renewed research attention over the last years in the context of social media.  In contrast to diseases or computer viruses, which we aim to contain and stop, the goal of viral marketing is to spread widely, reaching the largest possible fraction of a community.

What makes viral marketing unique?
But some aspects of viral marketing are very different from what we see in other spreading phenomena. First of all, there are many platforms that can be used to spread information at the same time, and the interaction between these platforms is not always transparent. Human psychology is a crucial factor in social networks, as repeated interaction and saturation can decrease the willingness to further spread viral content. Marketing campaigns have a limited budget, and therefore it is meaningful to understand how we can use incentives and how efficient they are. This also means that it is essential to find the group of most influential people that can be used as seeds for the viral campaign.

Network science has addressed to a great extent all these individual questions, mostly under the assumption of full knowledge of the connections between the agents and their influence. Currently, so-called multiplexes are an active research field that studies the behavior of multi-layer networks. This research unveils the relationships between the dynamics of viral marketing, the connection pattern, and strength between the network layers. Although viral spreading may be unachievable in a single layer, for example a social network like Facebook, the critical threshold may be exceeded by joining different platforms. Within a given platform, people alike can be clustered using community detection algorithms. Once the communities are identified, influence maximization algorithms have been established to select these persons that maximize the spread of viral content. Although this discrete optimization problem is computationally difficult—or NP-hard—mathematicians have proposed algorithms that can efficiently predict who to target to give a campaign the best chance of going viral. On top of that, optimal pricing strategies have been developed to reward recommenders.

The FotoQuest Austria app aims to engage citizen scientists in their campaign - network theory may help them go "viral." © IIASA

The FotoQuest Austria app aims to engage citizen scientists in their campaign – network theory may help them go “viral.” © IIASA

Although the literature is extensive, the nature of the results is often theoretical and involves mathematically complex models and algorithms. Considering that only partial information on the network is usually available, it is not straightforward to bring this knowledge back to a practical marketing campaign. So researchers in this field are trying to bridge the gap between theoretical results and practical problems. The generic, powerful methods of network science are sufficiently versatile to capture the specifics of real-world applications. As such, network science can provide guidelines that can bring great value for the design of heuristic methods in marketing strategies.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Black swan sandwich: From one risk to layered risks

By Leena Ilmola-Sheppard, IIASA Advanced Systems Analysis (ASA) Program

Crisis management problems are getting more complex and complicated, but at the same time, governments have less and less resources for their management. How can research help decision makers plan for the unplannable?

Last week in Geneva,  I took part in a crisis management workshop for national decision makers organized by the OECD High Level Risk Forum and the Swiss Federation Chancellor  While the meeting was very specific to national security and crisis management, I found some takeaway messages that are relevant to us researchers as well, especially for those of us that hope that to help decision makers make better decisions through modeling.

leena-pics

Mads Ecklon, Head of the Centre for Preparedness Planning and Crisis Management of the Danish Emergency Management Agency, used the figure above as a framework to explain crisis management. His message can also be applied to the development of any social system.  Picture 1 describes the standard starting point of the modeling exercise. We are modeling one behavior and then analyze how the system performance develops in a controlled situation. Ecklon explained that potential futures are not so predictable: the crisis in hand can either be solved, solved only partially, not solved at all, or in the worst case the problem may escalate (you never know how a social system will react in the crisis situation—a small incident can turn into a massive riot).  The challenge for both national level crisis managers and modelers is same; you have to take all of these potential developments into a consideration.

But what happens if a new, unexpected crisis pops up while all attention is focused on the initial problem?  Such hard-to-predict events are often referred to as “black swan events.” Eclon said that their team has more frequently been seeing situations where, when attention is focused on the current crisis, a new, different or related, crisis develops and no one notices it.  For example, in the UK in 2007, just when all the crisis management resources were invested in flooding crisis, foot and mouth disease broke out among cattle.  The new phenomenon, Ecklon  claimed, is that these crises are piling up and even if they are independent from each other, the joint impact can be disastrous.

Leena5

Modeling black swan events
I think that this message is important for modelers as well.  We may be very happy to model all the four windows of our comic strip. But how can we include new surprises and crises into an ongoing model?   We should develop models that include different development trajectories triggered by a change in one of our variables, but simultaneously we should be able to account for several overlapping surprises.

In the meeting, national risk managers spoke about ”unknown unknowns,” low probability high impact risks–strange unforeseen animals like a black swan that jump on the plate just when we think that the situation is in some kind of control.

This kind of modeling challenge is fascinating from an academic perspective, but researchers’ intellectual hunger should not be the only reason to develop methods for these kinds of situations.  From decision makers’ perspective, this is exactly the case where useful models are needed. The multiple simultaneous developments of the complex systems are difficult to capture even for the brightest of the crisis teams, but a model could manage a job very well.

Most of the IIASA models are large, integrated models that cover global systems. These models are not designed for digesting black swan sandwiches.  The Danish crisis management team has a solution worth for benchmarking for this problem as well. They have a specific small team that is called a Pandora’s Cell.  Pandora’s Cell is dedicated to anticipating, imagining, and scanning for potential not-so-obvious developments that should be taken into consideration in decision making. This dedicated team is needed because all the other resources available have been focused on the obvious events, as described in the square one of our comic strip.

dreamstime_xl_47204013

Black swan events refer to those that are unpredictable and difficult to plan for. © Wrangel | Dreamstime.com – Black Swan Photo

What do our models really represent?

By Dan Jessie, IIASA Research Scholar, Advanced Systems Analysis Program

As policymakers turn to the scientific community to inform their decisions on topics such as climate change, public health, and energy policy, scientists and mathematicians face the challenge of providing reliable information regarding trade-offs and outcomes for various courses of action. To generate this information, scientists use a variety of complex models and methods. However, how can we know whether the output of these models is valid?

This question was the focus of a recent conference I attended, arranged by IIASA Council Chair Donald G. Saari and the Institute for Mathematical Behavioral Sciences at the University of California, Irvine. The conference featured a number of talks by leading mathematicians and scientists who research complex systems, including Carl Simon, the founding Director of the University of Michigan’s Center for the Study of Complex Systems, and Simon Levin, Director of the Center for BioComplexity at Princeton University. All talks focused on answering the question, “Validation. What is it?”

To get a feel for how difficult this topic is, consider that during the lunch discussions,  each speaker professed to know less than everybody else! In spite of this self-claimed ignorance, each talk presented challenging new ideas regarding both specifics of how validation can be carried out for a given model, as well as formulations of general guidelines for what is necessary for validation.

How closely does a model need to mirror reality? © Mopic | Dreamstime.com - Binary Background Photo

How closely does a model need to mirror reality? © Mopic | Dreamstime.com – Binary Background Photo

For example, one talk discussed the necessity of understanding the connecting information between the pieces of a system. While it may seem obvious that, to understand a system built from many different components, one needs to understand both the pieces and how the pieces fit together, this talk contained a surprising twist: oftentimes, the methodology we use to model a problem unknowingly ignores this connecting information. By using examples from a variety of fields, such as social choice, nanotechnology, and astrophysics, the speaker showed how many current research problems can be understood in this light. This talk presented a big challenge to the research community to develop the appropriate tools for building valid models of complex systems.

Overall, the atmosphere of the conference was one of debate, and it seemed that no two speakers agreed completely on what validation required, or even meant. Some recurring questions in the arguments were how closely does a model need to mirror reality, and how do we assess predictions given that every model fails in some predictions? What role do funding agencies and peer review play in validation? The arguments generated by the talks weren’t limited to the conference schedule, either, and carried into the dinners and beyond.

I left the conference with a sense of excitement at seeing so many new ideas that challenge the current methods and models. This is still a new and growing topic, but one where advances will have wide-ranging impacts in terms of how we approach and answer scientific questions.

IIASA Council Chair Don Saari: Validation: What is it?

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

How can research help achieve resilience?

By Elisabeth Suwandschieff, Research Scholar, IIASA Ecosystems Services and Management Program

IMG_3114

Vienna, Austria

We live in a world that is fluid and diverse. Yet policymakers have to find solutions to problems that are definitive and effective, able to adapt to uncertain, changing, and challenging environments. How can research help policymakers to achieve such resilience?

At last week’s 4th Viennese Talks on Resilience and Networks, I listened to a number of talks on this topic from prominent figures in politics, military, research, and the private sector who came together to discuss future potential pathways for Austria. Speakers from politics emphasized the importance of social solutions such as greater investment in education. Meanwhile researchers from IIASA and other institutions brought perspective from systems analysis methods and explained how research on dynamic systems can inform policy making.

System dynamics view
From the research perspective, IIASA’s Brian Fath and others brought a systems analytical view of complex systems and their dynamics. They explained that complex systems such as organizations, businesses, and cities go through different stages in their “ecocycle.” Understanding the cycle and process is key to influencing its development.

FAS.research Director Harald Katzmair argued that life, as a complex system, can be seen as a process of growth, stagnation, destructurization and reorganization. In a recent research project, Katzmair found that the main factor in achieving resilience was the ability of the system to remain flexible through improvisation, collaboration, behavioral change and openness. If we apply this to our understanding of the world it becomes necessary to rethink our approach to leadership in every aspect.

“Our world is not a closed system; it does not consist of one choice, one idea, one currency,” said Katzmair.

Fath said that resilience is achieved by successfully managing each stage of the life cycle, explaining that even collapse can be seen as a key feature of system dynamics, because it results in developmental opportunities. Through disturbance and adaptive change in the landscape, new landscapes can be shaped.

Applying research to resilience
Many of the research talks were mathematical and complex. How can such research help in achieving resilience on a practical level? The issue for policymakers is that they have to provide definitive solutions when actually we live in a world that is fluid and diverse – therefore we need a diversified portfolio of problem solving. That is, solutions must be broad without losing focus. They must be effective, but remain flexible and open.

Research can bring different experiences together, provide a platform and a common language that can be shared. Systems thinking is a powerful way to condense the different ways of thinking and produce a portfolio of options rather than provide rigid solutions.

The adaptive cycle (Burkhard et al. 2011)

The adaptive cycle (Burkhard et al. 2011)

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.