Exploration and exploitation strategies. What kind of analytical models ?

This paper gives some insights related to the combination of exploration and exploitation behaviors. A recurrent question for firms deals with this blend of exploration and exploitation mechanisms. Firms are engaged in new activities like research and at the same time in more routine ones like development and production. Thus, they should find a satisfying arrangement between exploitation. But in order to do that, they should better understand their working. This paper analyzes adaptive systems through exploration and exploitation behaviors of firms. In order to better understand the temporal articulation of those behaviors, we refer to a mapping representation of search processes using NK models (Kauffman, 1993).Evolutionary approaches of firms, exploration and exploitation behaviors, NK models.

Evolutionary modeling in economics : recent history and immediate prospects

Abstract not availablemathematical economics and econometrics ;

The interpretations and uses of fitness landscapes in the social sciences

__Abstract__ This working paper precedes our full article entitled “The evolution of Wright’s (1932) adaptive field to contemporary interpretations and uses of fitness landscapes in the social sciences” as published in the journal Biology & Philosophy (http://link.springer.com/article/10.1007/s10539-014-9450-2). The working paper features an extended literature overview of the ways in which fitness landscapes have been interpreted and used in the social sciences, for which there was not enough space in the full article. The article features an in-depth philosophical discussion about the added value of the various ways in which fitness landscapes are used in the social sciences. This discussion is absent in the current working paper. Th

Optimal modularity: A demonstration of the evolutionary advantage of modular architectures

Modularity is an important concept in evolutionary theorizing but lack of a consistent definition renders study difficult. Using the generalised NK-model of fitness landscapes, we differentiate modularity from decomposability. Modular and decomposable systems are both composed of subsystems but in the former these subsystems are connected via interface standards while in the latter subsystems are completely isolated. We derive the optimal level of modularity, which minimises the time required to globally optimise a system, both for the case of two-layered systems and for the general case of multi-layered hierarchical systems containing modules within modules. This derivation supports the hypothesis of modularity as a mechanism to increase the speed of evolution. Our formal definition clarifies the concept of modularity and provides a framework and an analytical baseline for further research.Modularity, Decomposability, Near-decomposability, Complexity, NK-model, Search, hierarchy

Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World

Almost universally, wealth is not distributed uniformly within societies or economies. Even though wealth data have been collected in various forms for centuries, the origins for the observed wealth-disparity and social inequality are not yet fully understood. Especially the impact and connections of human behavior on wealth could so far not be inferred from data. Here we study wealth data from the virtual economy of the massive multiplayer online game (MMOG) Pardus. This data not only contains every player's wealth at every point in time, but also all actions of every player over a timespan of almost a decade. We find that wealth distributions in the virtual world are very similar to those in western countries. In particular we find an approximate exponential for low wealth and a power-law tail. The Gini index is found to be $g=0.65$, which is close to the indices of many Western countries. We find that wealth-increase rates depend on the time when players entered the game. Players that entered the game early on tend to have remarkably higher wealth-increase rates than those who joined later. Studying the players' positions within their social networks, we find that the local position in the trade network is most relevant for wealth. Wealthy people have high in- and out-degree in the trade network, relatively low nearest-neighbor degree and a low clustering coefficient. Wealthy players have many mutual friendships and are socially well respected by others, but spend more time on business than on socializing. We find that players that are not organized within social groups with at least three members are significantly poorer on average. We observe that high `political' status and high wealth go hand in hand. Wealthy players have few personal enemies, but show animosity towards players that behave as public enemies.Comment: 22 pages, 8 figures, 8 pages S

Essays on the co-evolution between strategies and technologies

Sensitivity, Innovation Attitudes, and Perseverance as the Strategic Foundations of Exaptation. Functions, Modular Architectures, and Technological Evolvability. A Generalized NK-Framework to Study the Co-Evolution Between Industry Dynamics and Artefact’s Architecture. Local Technological Evolution & University-Industry Collaboration

Statistical mechanics of complex networks

Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks.Comment: 54 pages, submitted to Reviews of Modern Physic

Understanding Innovation as a Collaborative, Co-Evolutionary Process

La innovació, que ha estat durant molt de temps el resultat, a vegades heroic, de la tasca d'un emprenedor solitari, està esdevenint progressivament una tasca col·lectiva que troba una descripció més acurada quan es presenta com el resultat d'un procés complex amb múltiples actors. Aquesta tesi vol explorar aquest aspecte col·lectiu de la innovació, tot aprofundint en dues línies de recerca. Una, que utilitza el modelatge basat en agents per a la creació de model teòrics. L'altre, que es basa en l'ús de l'anàlisi qualitatiu per a esbrinar algunes de les claus d'unes organitzacions ‐els Living Labs ‐ que cerquen involucrar els usuaris en el procés d'innovació. Ara bé, malgrat presentem la innovació com un procés obert, aquesta entesa com un procés tancat sembla també tenir èxit. De fet, tant els telèfons mòbils molt simples o molt complexos, semblen seguir aquest enfocament. En quines condicions el procés d'innovació es beneficia de ser un procés obert i quan és possible obtenir millors resultats retenint el control de la totalitat del procés, és la nostra primera pregunta de recerca. D'altra banda, aquest procés de col·laboració, característic d'un enfocament obert, és considerat normalment a un nivell micro com el resultat de la interacció diàdica entre agents. Existeix però, un altre nivell, un nivell macro que ve caracteritzat per la funció d'institucions com les Escoles de Negocis, que juguen un paper important en destil·lar les millors pràctiques i crear hipòtesis a partir d'elles que si es revelen exitoses seran adoptades per la totalitat dels agents. La comprensió del funcionament d'aquest procés, del nombre de casos que cal considerar i de quan extensius han de ser, entendre fins a quin punt les empreses poden confiar en l'assessorament de les Escoles de Negoci i quan es necessari aventurar‐se en l'exploració de noves possibilitats, és també quelcom necessari per a caracteritzar la innovació com un procés col·lectiu. Malauradament, la nostra comprensió dels mecanismes col·laboratius és encara escassa. Sabem però, que la innovació ja no és quelcom exclusiu dels laboratoris d'I+D o d'organitzacions capdavanteres, sinó que els usuaris juguen no solament un paper rellevant sinó que són percebuts com a actors amb un gran potencial. Els Living Labs és una de les tentatives per proporcionar estructura i governança a la involucració dels usuaris en el procés d'innovació. En aquest aspecte, examinarem quina és la contribució d'aquests usuaris i com els Living Labs busquen capturar‐ne el seu coneixement i aplicar‐lo i quant tenen èxit en aquest procés.La innovación, que se ha presentado muchas veces como el resultado de un proceso, muchas veces heroico, de emprendedores excepcionales, se está convirtiendo de una forma progresiva en un proceso colectivo que se describe con más acierto cuando se presenta como el resultado de un proceso complejo con multitud de actores. Esta tesis, pretende explorar este aspecto colectivo del proceso de innovación, profundizando en dos líneas de investigación. Una que utiliza el modelado basado en agentes para la construcción de modelos teóricos. Otra que se basa en el análisis cualitativo para profundizar en las claves de unas organizaciones ¬los Living Labs ‐ que buscan involucrar a los usuarios en los procesos de innovación. Ahora bien, a pesar de que la innovación se presente como un proceso abierto, ésta entendida como un proceso cerrado, parece también tener éxito. De hecho, los teléfonos móviles muy simples o muy complejos, parecen seguir este enfoque. En qué condiciones el proceso de innovación se beneficia de ser un proceso abierto y cuando es posible obtener mejores resultados reteniendo el control de la totalidad del proceso, es nuestra primera pregunta de investigación. Por otro lado, este proceso de colaboración, característico de un enfoque abierto, es considerado normalmente a un nivel micro, como el resultado de la interacción diádica entre agentes. Existe pero, otro nivel, un nivel macro, caracterizado por la función de instituciones como las Escuelas de Negocios, que juegan un papel importante destilando las mejores prácticas y creando hipótesis a partir de ellas que si se revelan exitosas serán masivamente adoptadas. La comprensión del funcionamiento de este proceso, del número de casos a considerar y de su extensión, comprender hasta qué punto las empresas pueden confiar en el asesoramiento de las Escuelas de Negocios y cuando es necesario aventurarse en un proceso de exploración de nuevas posibilidades, es también algo imprescindible para caracterizar la innovación como un proceso colectivo. Desgraciadamente nuestra comprensión de los mecanismos colaborativos en la innovación es aún escasa. Sin embargo sabemos que la innovación ya no es algo exclusivo de los laboratorios de I+D o de grandes empresas, los usuarios juegan no sólo un papel relevante sino que son percibidos como actores con un alto potencial. Los Living Labs es una de las tentativas que buscan proporcionar estructura y gobierno a la involucración de los usuarios en el proceso de innovación. En este aspecto, examinaremos cuál es la contribución de los usuarios, cómo los Living Labs buscan capturar su conocimiento y aplicarlo y cuando tienen éxito en su intento.Innovation, which used to be the result of a single, sometimes heroic, entrepreneur, is progressively turning into a collaborative endeavor, better described as the result of a complex process with multiple actors. This thesis aims to explore this collaborative aspect of innovation by digging into two strands of research. One uses Agent‐Based Modeling to create theoretical models, where the other one uses qualitative analysis to devise some insights from organizations ‐Living Labs ‐that aim to involve users in innovation. In addition to understanding innovation as an open process, a closed one seems sometimes to be equally successful. In fact, very simple and very complex mobile phones seem to follow this later approach. Under what conditions innovation benefits from being open and when better results can be obtained from retaining control of the whole process is our first research question. This process of collaboration, characteristic of the open approach, is normally considered at a micro level, as a result of a dyadic interaction between agents. Nevertheless, there is a macro level characterized by institutions, such as Business Schools, that play an important role in uncovering Best Practices and building hypothesis that, if successful, will be adopted by the agents. Understanding how this process works; how many cases should be collected and how comprehensive they should be; how much companies can rely on the insights of Business Schools; and when it is necessary to engage in exploration, is also necessary when characterizing innovation as a collective process. The mechanisms of collaboration are, however, not all well‐understood. Innovation is no longer in the solely hands of R&D laboratories or even organizations, users play an increasingly significant role and are being perceived as holding vast potential. Living Labs is one attempt to provide structure and governance to user involvement in innovation. Here, we will examine what is the contribution of users, how Living Labs aim to capture relevant knowledge and apply it, and when and how this proves successful