Post-Industrial Economics, Service-Systems Engineering, Knowledge-Market Design

"Prediction markets could be used as a tool to aggregate and evaluate information, a kind of "weak crystal ball" that could help lawmakers make more informed decisions.
...
The idea is rather than taking a survey to get the average opinion and relying on the wisdom of crowds, the prediction market identifies the wisdom in crowds because the market only attracts participants who feel confident enough in their predictions that they are willing to put money on the line. Prediction markets give participants a financial incentive to get things right."
http://www.miller-mccune.com/politics/government-prediction-markets-3656/

Jacques Fresco on the problem of superstitious ignorance
http://www.youtube.com/watch?v=EXWnFeG5EyA

"There are four types of knowledge services: generate content, develop products, provide assistance, and share solutions. Knowledge services are modeled as a circular value chain comprising nine stages that embed, advance, or extract value from knowledge-based products and services. The stages are: generate, transform, manage, use internally, transfer, enhance, use professionally, use personally, and evaluate. (Simard, 2007) described a rich to reach service delivery spectrum that is segmented into categories of recipients, with associated levels of distribution, interactions, content complexity, and channels. The categories, from rich to reach, are: unique (once only), complex (science), technical (engineering), specialized (professional), simplified (popular), and mandatory (everyone).

From the perspective of knowledge markets, Mcgee and Prusak (1993) note that people barter for information, use it as an instrument of power, or trade it for information of greater value. Davenport and Prusak (1998) used a knowledge marketplace analogy to describe the exchange of knowledge among individuals and groups. However, Shapiro and Varian (1999) indicate that information markets will not resemble textbook competitive markets with many suppliers offering similar products but lacking the ability to influence prices. Simard (2006) described knowledge markets as a group of related circular knowledge-service value chains that function collectively as a sector, to embed, advance, and extract value to yield sector outcomes and individual benefits."
http://en.wikipedia.org/wiki/Knowledge_market#Knowledge_services

"In large research organizations there is a tendency for new research projects to originate in knowledge silos. Applied research faces growing challenges of how to consider the needs of the customers, scientific knowledge and societally relevant questions in research projects. Service science is an emerging research interface, in which participation from different disciplines, such as design, business needed. In front of these challenges collaboration across the silos, hierarchical levels, disciplines and different actors is indispensable. We claim that multifaceted collaboration does not emerge without specific efforts. Cross-disciplinary research requires network processes for initiating learning, synergy and collaboration. We analyse a method aiming at co-creation in a multidisciplinary research network. We focus especially on how this interactive and cocreative process promotes the crossing of borders of knowledge silos."
http://www.cba.neu.edu/uploadedFiles/Site_Sections/OLKC_2010/Program_Overview/Parallel_Sessions/124_Halonen_Full%20Paper_326_Crossing%20the%20borders%20of%20knowledge%20silos%20in%20Service%20Science%20anf%20Business%20network.pdf

"At the most basic level, a job is essentially a set of incentives. As a person acts according to those incentives, he or she performs work that is currently required in order to produce products and services. In the economy of the future, if that work is no longer required, we will need to create “virtual” jobs. In other words, people will continue to earn income by acting in accordance with incentives, but their actions will not necessarily result in “work” in the
traditional sense."
http://www.thelightsinthetunnel.com/

"In The Future of Work, renowned organizational theorist Thomas W. Malone, codirector of MIT’s landmark initiative “Inventing the Organizations of the 21st Century,” shows where these things are already happening today and how—if we choose—they can happen much more in the future. Malone argues that a convergence of technological and economic factors—particularly the rapidly falling cost of communication—is enabling a change in business organizations as profound as the shift to democracy in governments. For the first time in history, says Malone, it will be possible to have the best of both worlds—the economic and scale efficiencies of large organizations, and the human benefits of small ones: freedom, motivation, and flexibility."
http://ccs.mit.edu/futureofwork/

"Coordination may be defined as the process of managing dependencies between activities (Malone & Crowstone, 1994). The need for coordination arises from the fact that literally all organizations are a complex aggregation of diverse systems, which need to work or be operated in concert to produce desired outcomes. To simplify the picture, one could decompose an organization into three broad components of actors, goals and resources. The actors, comprising of entities such as management, employees, customers, suppliers and other stakeholders perform interdependent activities aimed at achieving certain goals. To perform these activities, the actors require various types of inputs or resources. As explained later in the paper the inputs may themselves be interdependent in the ways that they are acquired, created or used. The goals to which the actors aspire are also diverse in nature. Some of them will be personal while others are corporate. Even where the goals are corporate, they address different sets of stakeholders and may be in conflict.

Calls for coordination are evident is situations where a) temporality is a factor, such that effects of delays or of future consequences of today’s decisions are not immediately apparent b) there is a large number of actors c) there is a large number interactions between actors or tasks in the system or d) where combinations or occurrences in the system involve an aspect of probability (stochastic variability). In summary, the more complex the system (and organizations are complex aggregations) the more coordination is necessary.

Multiple actors and interactions, resources and goals need to be coordinated if common desired outcomes are to be achieved. Viewed from the need to maintain perspective and solve problems that might arise from these multiplicities, coordination links hand in glove with the concept of systems thinking."
http://en.wikibooks.org/wiki/Systems_Theory/Coordination

What is Coordination Theory and How Can It Help Design Cooperative Work Systems:
http://crowston.syr.edu/system/files/10.1.1.92.4445.pdf

A Coordination Theory Approach to Organizational Process Design:
http://orgsci.journal.informs.org/content/8/2/157.abstract

Perspectives on Mechanism Design in Economic Theory:
http://www.nobelprize.org/nobel_prizes/economics/laureates/2007/myerson_lecture.pdf

Coordinating Mechnisms in Care Provider Groups: Relational Coordination as a Mediator and Input Uncertainty as a Meditor of Performance Effects:
http://www.jstor.org/pss/822615

Mechanism Design for Automated Negotiation and its Application to Task Oriented Domains:
http://www.dia.fi.upm.es/~phernan/AgentesInteligentes/referencias/zlotkin96.pdf

Electronic Markets and Electronic Heirarchies:
http://is.esade.edu/faculty/wareham/Teaching/StratNetComp/Readings/Electronic%20Markets%20and%20electronic%20Hierarchies.pdf

The Promise of Prediction Markets:
http://www.arlingtoneconomics.com/studies/promise-of-prediction-markets.pdf

Market Engineering:
http://www.econbiz.de/archiv/ka/uka/information/market_engineering.pdf

"Mechanism design, an important tool in microeconomics, has recently found widespread applications in modeling and solving decentralized design problems in many branches of engineering, notably computer science, electronic commerce, supply chain management, network economics, and services science and engineering. Mechanism design is concerned with settings where a social planner faces the problem of aggregating the announced preferences of multiple agents into a collective decision when the agents exhibit strategic behavior."
http://lcm.csa.iisc.ernet.in/iisc-ibm-workshop/tutorials.html

"MS&E 181: Issues in Technology and Work for a Postindustrial Economy
How changes in technology and organization are altering work and lives. Approaches to studying and designing work. How understanding work and work practices can assist engineers in designing better technologies and organizations. Topics include job design, distributed and virtual organizations, the blurring of boundaries between work and family life, computer supported cooperative work, trends in skill requirements and occupational structures, monitoring and surveillance in the workplace, downsizing and its effects on work systems, project work and project-based lifestyles, the growth of contingent employment, telecommuting, electronic commerce, and the changing nature of labor relations.
...
MS&E 201: Dynamic Systems
Goal is to think dynamically in decision making, and recognize and analyze dynamic phenomena in diverse situations. Concepts: formulation and analysis; state-space formulation; solutions of linear dynamic systems, equilibria, dynamic diagrams; eigenvalues and eigenvectors of linear systems, the concept of feedback; nonlinear dynamics, phase plane analysis, linearized analysis, Liapunov functions, catastrophe theory. Examples: grabber-holder dynamics, technology innovation dynamics, creation of new game dynamics in business competition, ecosystem dynamics, social dynamics, and stochastic exchange dynamics.
...
MS&E 236H: Game Theory with Engineering Applications
Advanced and mathematically more rigorous version of MS&E 236. Strategic interactions among multiple decision makers emphasizing applications to engineering systems. Topics: efficiency and fairness; collective decision making and cooperative games; static and dynamic noncooperative games; and complete and incomplete information models. Competition: efficient markets; Bertrand, Cournot, and Stackelberg models. Mechanism design: auctions, contracts. Examples from engineering problems."
...
MS&E 248: Economics of Natural Resources
Intertemporal economic analysis of natural resource use, particularly energy, and including air, water, and other depletable mineral and biological resources. Emphasis is on an integrating theory for depletable and renewable resources. Stock-flow relationships; optimal choices over time; short- and long-run equilibrium conditions; depletion/extinction conditions; market failure mechanisms (common-property, public goods, discount rate distortions, rule-of-capture); policy options.
...
MS&E 299: Voluntary Social Systems
Ethical theory, feasibility, and desirability of a social order in which coercion by individuals and government is minimized and people pursue ends on a voluntary basis. Topics: efficacy and ethics; use rights for property; contracts and torts; spontaneous order and free markets; crime and punishment based on restitution; guardian-ward theory for dealing with incompetents; the effects of state action-hypothesis of reverse results; applications to help the needy, armed intervention, victimless crimes, and environmental protection; transition strategies to a voluntary society.
...
MS&E 302: Optimal Dynamic Systems
Controllability and observability, stabilizing feedback. Optimal control theory and the Pontryagin maximum principle; problems with inequality constraints, transversality condition, discounting cost, infinite horizon problem; the Hamilton-Jacobi-Bellman equation; stochastic control. Applications: optimal economic growth, control of predator/prey systems, spread of product innovation.
...
MS&E 336: Topics in Queuing Networks
Advanced efficient control and high-performance design of queuing systems involving job scheduling and resource (server) allocation. Dynamic and stochastic scheduling. Resource allocation in random environments. Real-time scheduling algorithms. Efficient control of queuing networks (routing, admission, flow control, etc.). Performance evaluation of complex queuing structures; identification of performance bottlenecks and techniques for alleviating them. General principles and methodology of high-performance design. Case studies and applications to the design of communication networks, high-speed switching, computer systems, flexible manufacturing systems, service systems, parallel and distributed processing networks, etc.
...
MS&E 336: Topics in Game Theory with Engineering Applications
Seminar. Recent research applying economic methods to engineering problems. Recent topics include: incentives in networked systems; mechanism design in engineered systems; and dynamics and learning in games.
...
MS&E 343: Optimal Control Theory with Applications in Economics
Classical and nonclassical optimal control applications in economics. Necessary and sufficient optimality conditions: maximum principle and HJB equation. Applications: single-person decision problems such as dynamic pricing, investment, marketing, and harvesting of renewable resources; multi-agent games such as dynamic oligopolies with open and closed-loop equilibria, capital accumulation, and dynamic pricing; and design of economic mechanisms such as screening contracts, regulation, and auctions.
...
MS&E 344: Applied Information Economics
The strategic acquisition, pricing, transfer, and use of information. Theoretical findings applied to real-world settings. Topics: optimal risk bearing, adverse selection, signaling, screening, nonlinear and state-contingent pricing, design of contests, incentives and organizations, strategic information transmission, long-run relationships, negative information value, research and invention, leakage and espionage, imperfect competition, information sharing, search and advertising, learning, and real-option exercise games."
http://explorecourses.stanford.edu/CourseSearch/m_search?page=0&q=MS%26E&filter-catalognumber-MS%26E=on

"We’re drowning in data. Bits are faster than atoms. Our jungle-surplus wetware can’t keep up. At least, not without Boyd’s help. In a society where every person, tethered to their smartphone, is both a sensor and an end node, we need better ways to observe and orient, whether we’re at home or at work, solving the world’s problems or planning a play date. And we need to be constantly deciding, acting, and experimenting, feeding what we learn back into future behavior.

We’re entering a feedback economy."
http://www.forbes.com/sites/oreillymedia/2012/01/05/goodbye-information-economy-hello-feedback-economy/

Humanist Community Forum (2011-10-23): Economic Issues from a Humanist Perspective (Hamid Javanbakht)

Hamid Javanbakht, a student studying service systems engineering and post-industrial economics, will be discussing how incentive-altruism and selfishness need not always be working at cross-purposes. The field of mechanism design seeks to set up compatible incentives which take into account the various preferences of local agents so that their actions not only profit themselves individually but also extend beyond their own interest to serve the global good. He will also be questioning whether morality is always effective at producing desirable behavior in cases where perverse incentives are built into the system such as finance and the military.
http://vimeo.com/32349025

Innovation in Large Service Systems in the Interest of Society

International Working Group on Services in HealthCare, Environment, Energy and Transportation

Executive Speaker Series

In the coming years, we anticipate a diverse and rich set of technologies and service systems that can sense and respond to the needs of the society in areas such as HealthCare, Environment, Energy, Transportation, Green Cars and others. We envision that such service systems will not only transform the way we live, but also dramatically change the underlying services economy.

This working group will ask a fundamental question: what does it take to design reliable, cost-efficient and manageable large service systems that can address the complex needs of the society. Examples of large service systems include healthcare service systems (e.g. remote home monitoring and tele-health), global supply chains, large environmental sensor systems (e.g. water management services), road traffic systems and large enterprises.
...
The working group intends to identify the technical, social and service systems deployment challenges by combining expertise from design, management, engineering, computer science, social sciences and operations research. It intends a focused effort using real-world case-studies that illustrate the interaction between technology, business processes, and human factors to solve problems related to improving patient care, quality of life, environment and more.
http://www.cmu.edu/silicon-valley/ilss/index.html

A Group Decision Making Method for Integrating Outcome Preferences in Hypergame Situations:
http://www.dss.dpem.tuc.gr/pdf/A%20Group%20Decision%20Making%20Method%20for%20Integrating.pdf

"The need to aggregate preferences occurring in many different disciplines: in welfare economics, where one attempts to find an economic outcome which would be acceptable and stable; in decision theory, where a person has to make a rational choice based on several criteria; and most naturally in voting systems, which are mechanisms for extracting a decision from a multitude of voters' preferences.  The framework for Arrow's theorem assumes that we need to extract a preference order on a given set of options (outcomes). Each individual in the society (or equivalently, each decision criterion) gives a particular order of preferences on the set of outcomes. We are searching for a preferential voting system, called a social welfare function (preference aggregation rule), which transforms the set of preferences (profile of preferences) into a single global societal preference order. The theorem considers the following properties, assumed to be reasonable requirements of a fair voting method:"  
http://en.wikipedia.org/wiki/Arrow's_impossibility_theorem

Advances in Hypergame Theory:
http://www.sci.brooklyn.cuny.edu/~parsons/events/gtdt/gtdt06/vane.pdf
Hypergame: A two-player game in which player 1 chooses any finite game and player 2 moves first. A pseudoparadox then arises as to whether the hypergame is itself a finite game. - Mathworld


On modeling value constellations to understand complex service system interactions:
http://www.cambridgeservicealliance.org/uploads/downloadfiles/serviceweekslides/2A%20-%20pmaglio-.pdf

"Maglio and Spohrer (2008) call for a multi-disciplinary approach – Service Science – to
understanding value co-creation in socio-technical systems. Service system (Spohrer et al., 2008) is a value co-creation configuration of resources that can be dynamically configured and connected to other service system’s resources. The service system is by nature complex and dynamic, involving people, technology, shared information, and value propositions connecting internal and external service systems (Maglio and Spohrer 2008). It is centered on provider–consumer interactions and is capable of improving its own state and the one of another system through acquiring, sharing or applying resources, with the aim of creating a basis for systematic service production and innovation. These resources can be competencies, knowledge, shared information, technology, people, and organizations."
http://www.requisiteremedy.com/docs/value-co-creation.pdf

"From service science perspective, value co-creation based on mutual understanding between customer and provider is one of fundamental importance. Service-dominant (S-D) logic is tied to the value-in-use meaning of value. The roles of providers and consumers are not distinct, meaning that value is co-created, jointly and reciprocally, also mutually beneficial relationship. However, at crucial points of interaction between customer and provider, where the co-creation experience occurs and where value is co-created, misunderstandings and service breakdowns can destroy the relationship. In this paper, we analyze formally how customer and provider are sharing internal model in the first phase of value co-creation model of service innovation, i.e., co-experience and co-definition. In co-experience, customer and provider perceived the value of each value proposition differently. Customer have an own internal model and so provider is, therefore co-experience is the most crucial feature of service system. Symbiotic hypergame analysis, in general explicitly assumes that the players involved possess subjective internal model of the environment including the counterparts. These assumptions convince us that it is the most adequate and convenient for describing value co-creation process by customer and provider. First, we categorizing customer and provider into the several types based on customer expectation and provider ability. Then, analyze formally using symbiotic hypergame analysis, how mutual understanding can be achieved between customer and provider. From the analysis, mutual understanding can be achieved as long as customer and provider have same interpretation, customer who has high expectation believes that provider is innovative and vice versa. It has been proven by analyzing Hyper Nash equilibrium in each scenario for pair of each type based on symbiotic hypergame analysis."
http://journals.isss.org/index.php/proceedings54th/article/viewFile/1378/483


"CouchSurfing is committed to facilitating intercultural understanding, personal development, and inspiring social experiences amongst the members of its global community. While other online networks help people connect to the friends they already have, CouchSurfing connects people to the new friends they would like to have, and even creates new connections between entire social groups. The community, which has millions of members and is growing fast, consists of people of all walks of life who are interested in hosting travelers in their homes, staying with locals while they travel, and meeting new people at events and social outings.

We became a B Corp because it provides the support for our mission that we would expect to find in the non-profit sector, while allowing us the freedom to innovate that more traditional for-profit companies enjoy.

Europe, North America, and South America are, as of August 2011, the regions with the largest numbers of CouchSurfing members. However, the community continues to reach more and more people in all areas of the world. In the year 2010, South America, Central Asia, Southeast Asia and the Middle East all experienced more than 90% growth rates in sign ups.

The Change We Seek™

CouchSurfing’s goal is to create inspiring experiences for their members that help them to explore the world, whether on the road or at home, and connect with one another. They believe that real social change starts with the individual, and that lasting education comes through personal experience. When people have the ability to reach out of their normal social interactions and spend time with people from different cultures and different backgrounds, they come to demolish their prejudices, from large to small.

The true power of their mission is that people can enrich their lives and the world around them through things that they already enjoy: fun, social contact, and the chance to have experiences that they’ll never forget.

They are committed to helping the world become more understanding, more connected, and more generous across all borders, be they physical or psychological."
http://bcorporation.net/couchsurfing

We believe university-level education can be both high quality and low
cost. Using the economics of the Internet, we've connected some of the
greatest teachers to hundreds of thousands of students all over the
world.
http://www.udacity.com/

In The Coming Education Revolution I discussed Sebatian Thurn and
Peter Norvig’s online AI class from Stanford that ended up enrolling
160,000 students. Felix Salmon has the remarkable update:

…there were more students in [Thrun's] course from Lithuania alone
than there are students at Stanford altogether. There were students in
Afghanistan, exfiltrating war zones to grab an hour of connectivity to
finish the homework assignments. There were single mothers keeping the
faith and staying with the course even as their families were being
hit by tragedy. And when it finished, thousands of students around the
world were educated and inspired. Some 248 of them, in total, got a
perfect score: they never got a single question wrong, over the entire
course of the class. All 248 took the course online; not one was
enrolled at Stanford.

Thrun was eloquent on the subject of how he realized that he had been
running “weeder” classes, designed to be tough and make students fail
and make himself, the professor, look good. Going forwards, he said,
he wanted to learn from Khan Academy and build courses designed to
make as many students as possible succeed — by revisiting classes and
tests as many times as necessary until they really master the
material.

And I loved as well his story of the physical class at Stanford, which
dwindled from 200 students to 30 students because the online course
was more intimate and better at teaching than the real-world course on
which it was based.

So what I was expecting was an announcement from Thrun that he was
helping to reinvent university education: that he was moving all his
Stanford courses online, that the physical class would be a space for
students to get more personalized help. No more lecturing: instead,
the classes would be taken on the students’ own time, and the job of
the real-world professor would be to answer questions from kids paying
$30,000 for their education.

But that’s not the announcement that Thrun gave. Instead, he said, he
concluded that “I can’t teach at Stanford again.” He’s given up his
tenure at Stanford, and he’s started a new online university called
Udacity. He wants to enroll 500,000 students for his first course, on
how to build a search engine — and of course it’s all going to be
free.
http://marginalrevolution.com/marginalrevolution/2012/01/udacity.html

Regional Coordination for Reduced Military Spending: Potential and Design:
http://users.ox.ac.uk/~econpco/research/pdfs/RegionalCoordforReducedMilitary.pdf

Intertemporal choice is the study of the relative value people assign to two or more payoffs at different points in time. This relationship is usually simplified to today and some future date. Intertemporal choice was introduced by John Rae in 1834 in the "Sociological Theory of Capital". Later, Eugen von Böhm-Bawerk in 1889 and Irving Fisher in 1930 elaborated on the model.
http://en.wikipedia.org/wiki/Intertemporal_choice

This book combines economic theory and design to create tools that economists can use to apply in social, political and institutional application.  This book seeks to provide the necessary stepping stones in order to facilitate the diffusion and adoption of this powerful tool for studying incentive structures in economics.  The book presents a number of examples, both theoretical and real-life. It also has a chapter that samples the literature that tests mechanisms away from the blackboard, in laboratories and the real world.
This book provides readers (students and applied economists) with the tools to design the rules of economics to harness the power of incentives.
http://books.google.com/books?id=dCRzDTT4HD4C&dq=mechanism+design+military+spending&output=html_text&source=gbs_navlinks_s

Banking: A Mechanism Design Approach

The authors study banking using the tools of mechanism design, without a priori assumptions about what banks are, who they are, or what they do. Given preferences, technologies, and certain frictions - including limited commitment and imperfect monitoring - they describe the set of incentive feasible allocations and interpret the outcomes in terms of institutions that resemble banks. The bankers in the authors' model endogenously accept deposits, and their liabilities help others in making payments. This activity is essential: if it were ruled out the set of feasible allocations would be inferior. The authors discuss how many and which agents play the role of bankers. For example, they show agents who are more connected to the market are better suited for this role since they have more to lose by reneging on obligations. The authors discuss some banking history and compare it with the predictions of their theory.
http://www.ssc.upenn.edu/~rwright/papers/RVW.pdf

"Too big to fail" is a colloquial term in regulation and public policy that refers to businesses dealing with market complications related to moral hazard, macroeconomics, economic specialization, and monetary theory.

According to this theory, certain financial institutions are so large and so interconnected that their failure will be disastrous to an economy. Proponents of this theory believe that these institutions should become recipients of beneficial financial and economic policies from governments or central banks to keep them alive. It is thought that companies that fall into this category take positions that are high-risk, as they are able to leverage these risks based on the policy preference they receive. The term has emerged as prominent in public discourse since the 2007–2010 global financial crisis.

Some critics see the policy as counterproductive and that large banks or other institutions should be left to fail if their risk management is not effective. Moreover, some assert that the "too big to fail" policy has been explicitly refuted in the People's Republic of China, with the insolvency of Guangdong International Trust & Investment Corporation in 1998.

Some economists, such as Nobel Laureate Paul Krugman, hold that economy of scale in banks, as in other businesses, as worth preserving, so long as they are well regulated in proportion to their economic clout, and therefore that "too big to fail" status can be acceptable. The global economic system must also deal with sovereign states being too big to fail.Others, such as Alan Greenspan, disagree: “If they’re too big to fail, they’re too big”.
http://en.wikipedia.org/wiki/Too_big_to_fail

"The liturgical system in Classical Athens (479–322 BCE) privately provided public goods, including naval defense. I use it to evaluate mechanism design policies and to address uncertainties in the historical record by adding predictive economic theory to research by ancient historians. I evaluate the system's success at meeting the conflicting goals of efficiency, feasibility, and budget balance by analyzing the Athenian citizens' incentives within a game of asymmetric information. In the game, multiple equilibria occur; citizens may or may not volunteer for duty or avoid it. I relate the game theoretic findings to historical events."
http://journals.cambridge.org/action/displayAbstract;jsessionid=3C85BAB6548B86F2D4E27D3B3864C219.journals?fromPage=online&aid=1031588

"Dean Gates’ current research focuses on game theory and mechanism design applied to both military manpower and acquisition. In military manpower, this research focuses on designing auctions to set retention and voluntary separation bonuses for military personnel using purely monetary incentives or individualized combinations of monetary and non-monetary incentives. This research has also developed a mechanism for setting assignment incentive pay to attract service members to hard-to-fill billets. In acquisition, this research focuses on incentive contracts, procurement auctions, contractor protests and technology transfer. Past research has involved policy analysis, cost-benefit analysis, burden-sharing in defense alliances, and government R&D and technology policy."
http://www.nps.edu/Administration/Deans/deans_GSPBB.html

Too Big to Know is about what happens to knowledge and expertise now that we are faced with the fact that there is way way way more to know than can be known by any individual. Its hypothesis is that knowledge and expertise are becoming networks, and are taking on the properties of networks.
http://www.toobigtoknow.com/

Market Engineering comprises the structured, systematic and theoretically founded procedure of analyzing, designing, introducing and also quality assuring of electronic market platforms as well as their legal framework regarding simultaneously their market mechanisms and trading rules, systems, platforms and media, and their business models. Market Engineering borrows concepts and methods from Economics, particularly, Game Theory, and Mechanism Design concepts, but also borrows concepts from Finance,Information Systems and Operations Research.
http://en.wikipedia.org/wiki/Market_engineering

The difficulty in designing and implementing electronic markets is oftentimes the interdependence of technical and economic objectives (Weinhardt et al. 2006). From an economic viewpoint, an electronic market must encompass common economic performance desiderata such as allocative efficiency. Relying on existing market mechanisms known from other contexts when constructing new markets may, however, result in poor efficiency (Lai 2005). The mechanism designer also has to account for the technical conditions of the target domain. To give an example, in case of a market for allocating Grid computing resources these conditions comprise the underlying environment in terms of Grid middleware and the requirements of potential Grid users and applications. The market should act as a resource allocation manager, hence, fulfilling general requirements upon such a manager. This allows the introduction of the precondition that a market apt for the Grid has to be realized as an electronic market. Otherwise, the market cannot fulfill an automated resource allocation as required by a Grid resource management system.
http://www.econbiz.de/archiv/ka/uka/information/market_engineering.pdf

Over the last couple of years, interest in prediction markets as a forecasting method has continuously increased in the scientific world and in industry. Markets provide incentives for information revelation and can be used as a mechanism for aggregating information. So far, prediction markets have done well in every known comparison with other forecasting methods. Whereas information aggregation is only a byproduct of most traditional markets, prediction markets are set up with the explicit purpose of soliciting information. Engineered carefully, prediction markets can directly guide decision making. This paper describes the fundamentals of prediction markets as well as their key design elements. We thereby aim at giving insights into design decisions which have to be made by prediction market operators. Moreover, we contribute to the literature by giving an extensive overview on fields of application of prediction markets which have been discussed in academic literature.
http://www.ksri.kit.edu/Upload/Publications/c0f28bf7-9b5c-4151-bce1-57f6095d5821.pdf

The research group Information & Market Engineering (IM) focuses on the challenges imposed by electronic markets and on the approaches used to meet these challenges. Our vision is to apply a well-defined and structured engineering process to create new markets and to re-engineer existing markets. The methodology of Market Engineering is a very promising way to design and implement new possible market structures combining the disciplines of economics, informatics and law. The basis for a deeper understanding of the research field Market Engineering is established through theories, methods and tools from these underlying disciplines.
http://www.ksri.kit.edu/Default.aspx?PageId=302&lang=en

http://www.im.uni-karlsruhe.de/

Prediction Markets versus Alternative Methods Empirical Tests of Accuracy and Acceptability
http://www.itas.fzk.de/deu/lit/2009/grae09a.pdf

Information Management and Market Engineering, Volume 1
http://books.google.com/books?id=vCywfD09AMwC&printsec=frontcover&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false

Duality arises in linear and nonlinear optimization techniques in a wide variety of applications.

Current flows and voltage differences are the primal and dual variables that arise when optimization and equilibrium models are used to analyze electrical networks. In economic markets the primal variables are production and consumption levels and the dual variables are prices of goods and services. In structural design methods tensions on the beams and modal displacements are the respective primal and dual variables..
http://dualityscience.com/yahoo_site_admin/assets/docs/cdgo2007_PDF.21362207.pdf

Minkowski Space-Time and Thermodynamics
http://philsci-archive.pitt.edu/4278/1/Minkowski_Spacetime%26Thermodynamics.pdf

Design Theory
http://tinyurl.com/DesignTheory