8 research outputs found

    The ecology of technology : the co-evolution of technology and organization

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    In this day and age, arguing that technology is a powerful force that drives many economic processes is like preaching to the choir. Nevertheless, despite the widespread realization of the important role of technology in our modern day society, an intimate understanding of the process of technological change is still lacking. This study seeks to provide more insight into the concept of technological change by characterizing it as a socio-cultural evolutionary process of variation, selection and retention. According to this logic, variety (or novelty) is created by (random or non-random) mutations (i.e., organizations and individuals that (re-) combine existing components in novel ways). This variety is subsequently selected out by the stakeholders in the environment, such as individuals, organizations, and institutions. In other words, the variety is then retained in the structural characteristics of the environment, commonly referred to as organizational routines and technological paradigms. Finally, these structural characteristics subsequently provide the context in/from which new mutations (or variations) are created. From there, the cycle can be repeated. Because, nowadays, technology is mostly developed in an organizational context, the appropriate place to study technology and technological change is in the context of organization science, which is an academic discipline that studies all facets of organization. Even though technology deserves a central role in any organization theory, technology has not yet penetrated fully the domain of organization science. The only domain in which technology has a central role is within evolutionary economics, a school of economic thought that was influenced by evolutionary biology. Even though evolutionary economics has surely added much to our understanding of the process of technological change, in our view, this school of thought mainly concentrates its attention on idiosyncratic accounts of variety creation and their subsequent selection by the environment. Much less attention has been attributed to how the selection environment (or the structural characteristics thereof) determines the variety creation. Consequently, insights from organizational ecology, which has its center of gravity at the selection environment, can add value over and above the ones originating from evolutionary economics. The key source of inspiration of organizational ecology is bioecology, which makes it evolutionary economics’ counterpart in sociology. In this study, we therefore seek to close the evolutionary circle by developing a structural or ecological perspective of technological change. After all, holding both links between variety and selection in focus at the same time (i.e., how variety is selected by the environment, and how the selection environment facilitates and constrains the creation of variety) provides for a truly evolutionary model of technological change. Accordingly, we define our research objective as follows: Research objective: To develop an ecology of technology in organization science. Because this objective is rather vague and abstract, we formulate several research questions to provide more direction in our quest to fulfill our objective. We formulate our first research question as follows. Research question 1: What is the importance of biotechnology? Providing an answer to this research question is the subject of Chapter 2. As a means of introducing biotechnology, we first describe biotechnology’s central dogma (i.e., DNA as the building block of life). Moreover, we provide a timeline to get a certain feel of the history and evolution of biotechnology, and list numerous socio-economic trends to get an idea of the importance of biotechnology in society. These trends clearly illustrate that biotechnology drives important social and economic events. Next, we evaluate biotechnology’s position in the overall technological landscape. Our main finding is that, despite its sharply increasing societal and economic importance, biotechnology still has not yet conquered a place in the technological core of our society. Reviewing the developments within synthetic biology (in this domain, complex systems are designed by (re-)combining DNA into biological parts that represent biological functions and, as such, is the domain where all aspects of biotechnology come together), it becomes clear that biotechnology as a whole is not yet in the growth stage of technological convergence that is characterized by a stable configuration of component technologies (i.e., a dominant design). Moreover, on the basis of the future expectations of experts, we conclude that biotechnology is a strategic technology that is nowhere near its peak influence, and that we can expect the importance to increase even further over the coming years. Obviously, whether biotechnology can deliver on its promise and materialize the expectations of insiders is not certain. Even when biotechnology delivers on only a small part of the promise, though, its impact will already be gigantic. For example, consider the fact that, in a 2007 interview, Craig Venter – who is one of the most well-renowned biotechnologists today – said that, in 20 years time, synthetic genomics is going to become the standard for making anything (Aldhous, 2007). So, in conclusion, biotechnology is a technology that is still emerging and does yet not display a stable and predictable pattern of growth that characterizes mature (i.e., non-emerging) technologies. Our next research question thus is as follows. Research question 2: How to study the growth of an emerging technology? In Chapter 3, on the basis of ecological insights and principles, we develop a structural or systemic view towards technology, and hereby take into explicit account the embedded nature of technology. That is, we propose that it adds value to view technology as a system composed of a set of interdependent components (or subsystems). More specifically, by relying on density dependence theory from organizational ecology, we effectively develop a multilevel framework that can be used to empirically study emerging technologies. Moreover, we employ the concept of the technological niche from organizational ecology, with its associated dimensions of crowding (associated with processes of competition) and status (associated with processes of legitimation), and add diversity as a key dimension. Through sophisticated multivariate analysis of biotechnology patents from the United States Patent and Trademark Office (USPTO), we validate this model, which we label the ‘ecology of technology’. However, we also discover some anomalies, which point to the limitations of our model, the most important being its rather static nature. Because emerging technologies are characterized by fluid patterns of growth, a static model is a severe misrepresentation of the evolution of emerging technologies. Our next research question naturally follows from this. Research question 3: How to study the evolution of an emerging technology? On the basis of insights from evolutionary economics, Chapter 4 distinguishes between two stages of technological development, namely the stages of divergence and convergence (that connect nicely with the seed and growth stage of life cycle theory). The focal element is what is generally referred to as the deep structure (in the context of technology also commonly referred to as a dominant design) that facilitates cumulative changes by reducing uncertainty and enabling specialization and integration through standardization. The stage of divergence is characterized by the absence of a deep structure, while the stage of convergence is characterized by its presence. So, in the latter stage, there is a relatively stable configuration of the system’s component technologies that results in relatively stable and predictable patterns of growth. On the basis of these insights, we adapt our multi-level model to identify these different stages of development at the component level. More specifically, if there is a mutualistic relationship between a component and the system (i.e., if system density contributes positively to component entry), the component is argued to have a dominant design. As we are dealing with an emerging technology, our main interest lies in the transition from the initial seed stage of technological divergence (i.e., the absence of a deep structure) to a growth stage of technological convergence (i.e., the existence of a deep structure), or the creation of a deep structure. This means that we do not take into account the revolutionary transition from a stage of convergence into divergence (i.e., the maturity and decline stage in life cycle theory). Not only do we refine our predictions regarding the effects of our existing dimensions (i.e., multilevel density dependence, crowding, status, and focal diversity), but, by further taking into account the lineage of technology, we refine our dimension of diversity by adding antecedent and descendant diversity as additional dimensions to the technological niche. This results in an intricate model that can be used to study the growth and evolution of an emerging technology. We demonstrate this by an empirical investigation of biotechnology patents from the USPTO and hereby provide further support for our ‘ecology of technology’. In the light of our research objective, before we answer the question of what the precise consequences are for organizations, we ask ourselves how we can effectively integrate our findings at the organizational level of analysis. We thus formulate our next research question accordingly. Research question 4: How can we integrate technology into the theory of the organization specifictechnological niche? In Chapter 5, we use a process of logical formalization to represent the theory of the organization-specific technological niche in a formal logical language. The reason for doing so is threefold. First, this forces us to explicate all underlying assumptions and to remove any inconsistencies to make the argument logically sound. Second, this requires us to supplement the theory so that it is complete, without missing elements. Third and finally, it results in a logically sound and complete theory fragment ready for extension by integrating the insights from the study of the evolution of technology. We choose nonmonotonic logic as the language in which we represent our arguments because nonmonotonic logic is better suited for theory building, and this connects better to the current wave of formalization in non-monotonic logic in organizational ecology. On the basis of this analysis, we already make two important theoretical extensions. First, by distinguishing between crowding in technological and market space, we tie technological crowding to both competition and legitimation. To be precise, technological crowding results in competition mainly if the crowding organization is a competitor of the focal organization. Second, uncertainty mediates the relationship between the perceived and actual technological quality of the organization. More specifically, under uncertainty, the actual quality of an organization’s technology cannot be readily observed so that resource controllers have to rely on status (i.e., historic technological quality) instead. With this formalized, logically sound and complete theory fragment in hand, we can turn to the question of the organizational consequences. We thus pose our next research question as follows. Research question 5: What are the consequences of integrating several technological insights into thetheory of the organization-specific technological niche? In Chapter 6, we integrate four technological insights from Chapters 3 and 4 into our formalized theory fragment from the previous chapter. These insights are: (1) multiple technological domains exist that have (2) different stages of development, (3) different levels of uncertainty, and (4) different growth rates. On the basis of these four insights, we extend the theory of the organization-specific technological niche considerably. For crowding, we demonstrate that the effect of crowding is not only conditional upon the identity of the other organization, but also on the stage of technological development. We also add non-crowding to the mix. Regarding the effect of (non-)crowding, in the stage of divergence, multiple competing design configurations exist, and crowding (non-crowding) increases (decreases) the competitiveness of the supported design configuration, having a legitimating (competition) effect. In contrast, in the stage of convergence, crowding (non-crowding) loses its legitimating (competition) function and results in competitive (legitimation) pressure. For status, the most important consequences are that: (1) status is domain dependent, and (2) its effect is dependent upon the stage of technological development (i.e., the effect of status is higher in the stage of divergence). We also add two additional dimensions, which are (1) technological opportunities (that can be represented by the growth rate of the domain), and (2) technological diversity (measured by the distribution of activities over alternative domains). By operationalizing performance as a two-dimensional vector, we suggest that the dimensions of the technological niche are related to different performance measures in distinct temporal relationships. However, even though this theoretical extension is certainly valuable, the subsequent question is whether these extensions hold when subjected to advanced empirical tests. We therefore formulate our next research question as follows. Research question 6: Can we find proof for our extended theory of the organization-specific technological niche? In Chapter 7, we empirically test several of our theoretical extensions of the organization-specific technological niche. Our dependent variable is biotechnology innovation (i.e., the number of biotechnology patents). Through a sophisticated empirical analysis, we find strong support for our extended theory. However, we also encounter some inconsistencies and anomalies. This seems to connect to the fact that processes of competition and legitimation are more appropriately defined at lower levels of analysis (i.e., at the component instead of at the system level). Moreover, due to the dual role of a direct technological tie (i.e., it can have both a competing and a legitimating function) that forms the basis for our measure of status, status is better defined at the component level of analysis. In contrast, biotechnological quality can be aggregated to the system level without losing significance. We thus find strong support for this dimension. Furthermore, we also clearly demonstrate the importance of taking into account the different dimensions of technological diversity (i.e., antecedent, focal, and descendant), with a vital role for antecedent diversity, which logically connects with the notion of absorptive capacity. The subsequent question is what this means for the broader academic debate regarding the (co-)evolution of technology and organization. We formulate our next research question accordingly. Research question 7: What are the implications for the study of the (co-)evolution of technology and organization? In the final chapter of this dissertation, we start by stating the main contribution of this dissertation, which is that we develop a dynamic multilevel model that can be used to empirically study the evolution of an emerging technology. As this model is based on the assumption that technology can effectively be studied as a system composed of an interacting set of components, we pay explicit attention to the embedded nature of technology. Hence, when studying the evolution of technology, it is inappropriate to focus on a single level of analysis and using a multilevel perspective adds value over and above any single level study. That is, technology (e.g., biotechnology) is composed of a set of technological components (e.g., biotechnology’s component technologies) while, at the same time, being embedded in a larger technological system (i.e., technological landscape). It is precisely this multilevel nature of technology that gives it the potential to close part of the chasm in the debate between organizational adaptation (i.e., the dominant perspective in evolutionary economics) and environmental selection (i.e., the dominant perspective in organizational ecology). More specifically, by defining technology at different levels of analysis (e.g., invention, component, system, and landscape), it is possible to tie the evolution of technology to the evolution of organization at different levels of analysis (i.e., individual organization, population of organizations, community, and society). This enables studying the evolution of technology and organization in unison, and thus provides the basis for a co-evolutionary model of technology and organization. Employing a multilevel perspective to both technology and organization at the same time, and defining technology and organization as nested hierarchies tied together at multiple levels of analysis, effectively allows an analyzes of how stable configurations travels upwards in this hierarchy. After all, "it is the information about stable configurations […] that guides the process of evolution" (Simon, 1952: 473)

    Archaeometrical study of mortars from public Roman structures in Verona

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    openThe city of Verona, located in the region of Veneto, in the north of Italy, had an important urban development during the Roman age. Due to its strategical position within the territory, the city counted with a particular importance, being this one of the key locations present in the norther territory of the roman empire. It is because of this high status possessed by the city that it counted with several public structures of great significance. Some of these structures, such as the Arena and part of the theatre are still standing, showing the implementation of remarkable construction techniques. This work aims to produce an archaeometrical characterize the mortars used in some of the most relevant constructions. For this purpose, mortar samples were extracted from the capitolium, the roman theatre, the odeum, the curia, the arena and from the city walls surrounding roman Verona. The samples were then analyzed through means such as x-ray powder diffraction (XRPD), colorimetry, optical microscopy, scanning electron microscope coupled with energy dispersive spectroscopy (SEM-EDS) and nuclear magnetic resonance (NMR). The obtained results were then analyzed and treated in order to obtain a clear understanding of the mortars present in the aforementioned structures.The city of Verona, located in the region of Veneto, in the north of Italy, had an important urban development during the Roman age. Due to its strategical position within the territory, the city counted with a particular importance, being this one of the key locations present in the norther territory of the roman empire. It is because of this high status possessed by the city that it counted with several public structures of great significance. Some of these structures, such as the Arena and part of the theatre are still standing, showing the implementation of remarkable construction techniques. This work aims to produce an archaeometrical characterize the mortars used in some of the most relevant constructions. For this purpose, mortar samples were extracted from the capitolium, the roman theatre, the odeum, the curia, the arena and from the city walls surrounding roman Verona. The samples were then analyzed through means such as x-ray powder diffraction (XRPD), colorimetry, optical microscopy, scanning electron microscope coupled with energy dispersive spectroscopy (SEM-EDS) and nuclear magnetic resonance (NMR). The obtained results were then analyzed and treated in order to obtain a clear understanding of the mortars present in the aforementioned structures

    Design of experiments for model-based optimization

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    Toward a theory of the evolution of business ecosystems : enterprise architectures, competitive dynamics, firm performance & industrial co-evolution

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.Cataloged from PDF version of thesis. Vita.Includes bibliographical references (v. 4, p. 698-745).This dissertation contributes toward the building of a theory of the evolution of business ecosystems. In the process, it addresses a question that has been posed by evolutionary theorists in the economics and sociology literatures for decades: "Why do firms in the same industry vary systematically in performance over time?" Seeking a systematic explanation of a longitudinal phenomenon inevitably requires characterizing the evolution of the industrial ecosystem, as both the organization (firm) and its environment (industry, markets and institutions) are co-evolving. This question is therefore explored via a theoretical sample in three industrial ecosystems covering manufacturing and service sectors, with competitors from the US, Europe and Japan: commercial airplanes, motor vehicles and airlines. The research is based primarily on an in depth seven-year, multi-level, multi-method, field-based case study of both firms in the large commercial airplanes industry mixed duopoly as well as the key stakeholders in their extended enterprises (i.e. customers, suppliers, investors and employees). This field work is supplemented with historical comparative analysis in all three industries, as well as nonlinear dynamic simulation models developed to capture the essential mechanisms governing the evolution of business ecosystems.(cont.) A theoretical framework is developed which endogenously traces the co-evolution of firms and their industrial environments using their highest-level system properties of form, function and fitness (as reflected in the system sciences of morphology, physiology and ecology), and which embraces the evolutionary processes of variation, selection and retention. The framework captures the path-dependent evolution of heterogeneous populations of enterprise architectures engaged in symbiotic inter-species competition and posits the evolution of dominant designs in enterprise architectures that oscillate deterministically and chaotically between modular and integral states throughout an industry's life-cycle. Architectural innovation - at the extended enterprise level - is demonstrated to contribute to the failure of established firms, with causal mechanisms developed to explain tipping points.by Theodore F. Piepenbrock.Ph.D

    Building on Progress - Expanding the Research Infrastructure for the Social, Economic, and Behavioral Sciences. Vol. 1

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    The publication provides a comprehensive compendium of the current state of Germany's research infrastructure in the social, economic, and behavioural sciences. In addition, the book presents detailed discussions of the current needs of empirical researchers in these fields and opportunities for future development. The book contains 68 advisory reports by more than 100 internationally recognized authors from a wide range of fields and recommendations by the German Data Forum (RatSWD) on how to improve the research infrastructure so as to create conditions ideal for making Germany's social, economic, and behavioral sciences more innovative and internationally competitive. The German Data Forum (RatSWD) has discussed the broad spectrum of issues covered by these advisory reports extensively, and has developed general recommendations on how to expand the research infrastructure to meet the needs of scholars in the social and economic sciences

    Spatial Approaches to the Political and Commercial Landscape of the Old Assyrian Colony Period

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    From the mid-20th century onwards, consolidated study of the merchant archives from the Old Assyrian trading colony at Kaneš (Kültepe) has not only transformed our understanding of the social, economic and political dynamics of the Bronze Age Near East, but also overturned many preconceived notions of what constitutes pre-modern trade. Despite this disciplinary impact and archaeological investigations at Kültepe and elsewhere, our understanding of this phenomenon has remained largely text-based and therefore of limited analytical scope, both spatially and contextually. The time is now right to reconsider it from a wider series of perspectives and this research project aims to do so via a combination of archaeological and computational approaches. The early Middle Bronze Age (Old-Assyrian colony period, ca. 1970-1700 BC) across central Anatolia and upper Mesopotamia was characterised by a network of long-distance overland exchanges. My research aims in this project are to re-assess the Old-Assyrian trade network in Upper Mesopotamia and Central Anatolia during the early Middle Bronze Age by reconsidering the archaeology of the region both on its own terms and via a range of computational approaches (including GIS and spatial statistics). My aim is to offer a sharper view of the fragmented political and economic situation in Upper Mesopotamia and Central Anatolia in the early Middle Bronze Age and evaluate how various environmental and economic factors could have affected the locations and the political and strategic importance of local city-states. Another important objective is to provide a model of the spatial distribution and the hierarchical organization of Assyrian commercial colonies in Anatolia and to reconstruct the ancient trade network in the relevant area
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