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Abstract:
This paper defines four basic business models based on what asset rights are sold (Creators, Distributors, Landlords and Brokers) and four variations of each based on what type of assets are involved (Financial, Physical, Intangible, and Human). Using this framework, we classified the business models of all 10,970 publicly traded firms in the US economy from 1998 through 2002. Some of these classifications were done manually, based on the firms' descriptions of sources of revenue in their financial reports; the rest were done automatically by a rule-based system using the same data. Based on this analysis, we first document important stylized facts about the distribution of business models in the U.S. economy. Then we analyze the firms' financial performance in three categories: market value, profitability, and operating efficiency. We find that no model outperforms others on all dimensions. Surprisingly, however, we find that some models do, indeed, have better financial performance than others. For instance, Physical Creators (which we call Manufacturers) and Physical Landlords have greater cash flow on assets, and Intellectual Landlords have poorer q's, than Physical Distributors (Wholesaler/Retailers). These findings are robust to a large number of robustness checks and alternative interpretations. We conclude with some hypotheses to explain our findings.

business models, performance

Abstract:
Over the past decade, the rise of the Internet has enabled the emergence of surprising new forms of collective intelligence. Examples include Google, Wikipedia, Threadless, and many others. To take advantage of the possibilities these new systems represent, it is necessary to go beyond just seeing them as a fuzzy collection of "cool" ideas. What is needed is a deeper understanding of how these systems work.

This article offers a new framework to help provide that understanding. It identifies the underlying building blocks - to use a biological metaphor, the "genes" - at the heart of collective intelligence systems. These genes are defined by the answers to two pairs of key questions:

- Who is performing the task? Why are they doing it? - What is being accomplished? How is it being done?

The paper goes on to list the genes of collective intelligence - the possible answers to these key questions - and shows how combinations of genes comprise a "genome" that characterizes each collective intelligence system. In addition, the paper describes the conditions under which each gene is useful and the possibilities for combining and re-combining these genes to harness crowds effectively.

Using this framework, managers can systematically consider many possible combinations of genes as they seek to develop new collective intelligence systems.

crowd courcing, wisdom of crowds, collective intelligence

Abstract:
This paper explores the possibility of solving supply chain capacity allocation problems using internal markets among employees of the same company. Unlike earlier forms of transfer pricing, IT now makes it easier for such markets to involve many employees, finegrained transactions, and frequently varying prices. The paper develops a formal model of such markets, proves their optimality in a baseline condition, and then analyzes various potential market problems and solutions. Interestingly, these proposed solutions are not possible in a conventional market because they rely on the firm's ability to pay market participants based on factors other than just the profitability of their market transactions. For example, internal monopolies can be ameliorated by paying internal monopolists on the basis of corporate, not individual, profits. Incentives for collusion among peers can be reduced by paying participants based on their profits relative to peers. Profit-reducing competition among different sales channels can be reduced by imposing an internal sales tax. And problems caused by fixed costs can be avoided by combining conditional internal markets with a pivot mechanism.

supply chain capacity, internal markets

Abstract:
This document discusses a few versatile, tool-like crowd performance algorithms necessary for humans to employ internet technologies to make better decisions collectively. This document also readily acknowledges that true collective intelligence approaches are foremost about organizational culture change and encouraging shared group norms (i.e., values) of sharing, openness, transparency, and collaboration. Humans will need to buy-in to the approaches and technology tools for any collective intelligence approach to work. The scope of this document has two sections:

The first section dives into some of the known theory and empirical evidence supporting a case that collective intelligence does, in fact, lead to better decision outcomes - specifically that collective intelligence employing recent advances in internet technologies can provide greater advantages than traditional organizational methods of making decisions.

The second section takes these underpinnings and then extends them to consider a tool and associated crowd performance algorithms that could be coupled into a packaged generic system that serves as a staging ground for an organization to launch collective intelligence efforts. This discussion considers how different features would be aligned with desired human and organizational factors, as well as what outcomes could be expected from such a generic system approach.

collective intelligence, diversity, algorithms, innovation, collaboration

Abstract:
Simulation modeling can be valuable in many areas of management science, but is often costly, time-consuming and difficult to do. This paper describes a new approach to simulation that has the potential to be much cheaper, faster and easier to use in many situations. In this approach, users start with a very simple generic model and then progressively replace parts of the model with more specialized "molecules" from a systematically organized library of predefined components. At each point, the system lets the user select from lists of possible substitutions, and then either automatically creates a new running model or shows the user where further manual changes are needed.

The paper describes an extensive experiment with using this approach to construct system dynamics models of supply chain processes in a large manufacturing company. The experiment included developing a comprehensive catalog of system dynamics molecules analogous to the periodic table in chemistry. The experiment also included developing an innovative "tangible user interface" with which users can create simulation models by moving actual physical objects around on a special table called a Sensetable. The paper concludes with a discussion of the benefits and limitations of this approach and how it could be used in other situations.

Simulation Modeling, Replacement, Specialization Hierarchy, Molecules, Tangible User Interface