Coordinating tasks in M-form and U-form organisations

We model the coordination of specialised tasks inside an organisation as "attribute matching". Using this method, we compare the performance of organisational forms (M-form and U-form) in implementing changes such as innovation and reform. In our framework, organisational forms affect the information structure of an organisation and thus the way to coordinate changes. Compared to the U-form, the M-form organisation achieves better coordination but suffers from fewer economies of scale. The distinctive advantage of the M-form is flexibility of experimentation, which allows the organisation to introduce more innovation and reform. The theory is illustrated by the organisational differences between China and the former Soviet Union and sheds light on their different reform strategies, particularly with regard to the prevalence of the experimental approach in China

Coordinating Tasks in M-Form and U-Form Organisations

We model the coordination of specialised tasks inside an organisation as "attribute matching". Using this method, we compare the performance of organisational forms (M-form and U-form) in implementing changes such as innovation and reform. In our framework, organisational forms affect the information structure of an organisation and thus the way to coordinate changes. Compared to the U-form, the M-form organisation achieves better coordination but suffers from fewer economies of scale. The distinctive advantage of the M-form is flexibility of experimentation, which allows the organisation to introduce more innovation and reform. The theory is illustrated by the organisational differences between China and the former Soviet Union and sheds light on their different reform strategies, particularly with regard to the prevalence of the experimental approach in China.Coordination, task, organisation, reform, innovation, China, Russia.

The Spatial Agent-based Competition Model (SpAbCoM)

The paper presents a detailed documentation of the underlying concepts and methods of the Spatial Agent-based Competition Model (SpAbCoM). For instance, SpAbCoM is used to study firms' choices of spatial pricing policy (GRAUBNER et al., 2011a) or pricing and location under a framework of multi-firm spatial competition and two-dimensional markets (GRAUBNER et al., 2011b). While the simulation model is briefly introduced by means of relevant examples within the corresponding papers, the present paper serves two objectives. First, it presents a detailed discussion of the computational concepts that are used, particularly with respect to genetic algorithms (GAs). Second, it documents SpAbCoM and provides an overview of the structure of the simulation model and its dynamics. -- Das vorliegende Papier dokumentiert die zugrundeliegenden Konzepte und Methoden des Räumlichen Agenten-basierten Wettbewerbsmodells (Spatial Agent-based Competition Model) SpAbCoM. Anwendungsbeispiele dieses Simulationsmodells untersuchen die Entscheidung bezüglich der räumlichen Preisstrategie von Unternehmen (GRAUBNER et al., 2011a) oder Preissetzung und Standortwahl im Rahmen eines räumlichen Wettbewerbsmodells, welches mehr als einen Wettbewerber und zweidimensionalen Marktgebiete berücksichtigt. Während das Simulationsmodell in den jeweiligen Arbeiten kurz anhand eines Beispiels eingeführt wird, dient das vorliegende Papier zwei Zielen. Zum Einen sollen die verwendeten computergestützten Konzepte, hier speziell Genetische Algorithmen (GA), detailliert vorgestellt werden. Zum Anderen besteht die Absicht dieser Dokumentation darin, einen Überblick über die Struktur von SpAbCoM und die während einer Simulation ablaufenden Prozesse zu gegeben.Agent-based modelling,genetic algorithms,spatial pricing,location model.,Agent-basierte Modellierung,Genetische Algorithmen,räumliche Preissetzung,Standortmodell.

Spatial competition of learning agents in agricultural procurement markets

Spatially dispersed farmers supply raw milk as the primary input to a small number of large dairy-processing firms. The spatial competition of processing firms has short- to long-term repercussions on farm and processor structure, as it determines the regional demand for raw milk and the resulting raw milk price. A number of recent analytical and empirical contributions in the literature analyse the spatial price competition of processing firms in milk markets. Agent-based models (ABMs) serve by now as computational laboratories in many social science and interdisciplinary fields and are recently also introduced as bottom-up approaches to help understand market outcomes emerging from autonomously deciding and interacting agents. Despite ABMs' strengths, the inclusion of interactive learning by intelligent agents is not sufficiently matured. Although the literature of multi-agent systems (MASs) and multi-agent economic simulation are related fields of research they have progressed along separate paths. This thesis takes us through some basic steps involved in developing a theoretical basis for designing multi-agent learning in spatial economic ABMs. Each of the three main chapters of the thesis investigates a core issue for designing interactive learning systems with the overarching aim of better understanding the emergence of pricing behaviour in real, spatial agricultural markets. An important problem in the competitive spatial economics literature is the lack of a rigorous theoretical explanation for observed collusive behavior in oligopsonistic markets. The first main chapter theoretically derives how the incorporation of foresight in agents' pricing policy in spatial markets might move the system towards cooperative Nash equilibria. It is shown that a basic level of foresight invites competing firms to cease limitless price wars. Introducing the concept of an outside option into the agents' decisions within a dynamic pricing game reveals viihow decreasing returns for increasing strategic thinking correlates with the relevance of transportation costs. In the second main chapter, we introduce a new learning algorithm for rational agents using H-PHC (hierarchical policy hill climbing) in spatial markets. While MASs algorithms are typically just applicable to small problems, we show experimentally how a community of multiple rational agents is able to overcome the coordination problem in a variety of spatial (and non-spatial) market games of rich decision spaces with modest computational effort. The theoretical explanation of emerging price equilibria in spatial markets is much disputed in the literature. The majority of papers attribute the pricing behavior of processing firms (mill price and freight absorption) merely to the spatial structure of markets. Based on a computational approach with interactive learning agents in two-dimensional space, the third main chapter suggests that associating the extent of freight absorption just with the factor space can be ambiguous. In addition, the pricing behavior of agricultural processors – namely the ability to coordinate and achieve mutually beneficial outcomes - also depends on their ability to learn from each other

Scalable ray tracing with multiple GPGPUs

Rapid development in the field of computer graphics over the last 40 years has brought forth different techniques to render scenes. Rasterization is today’s most widely used technique, which in its most basic form sequentially draws thousands of polygons and applies texture on them. Ray tracing is an alternative method that mimics light transport by using rays to sample a scene in memory and render the color found at each ray’s scene intersection point. Although mainstream hardware directly supports rasterization, ray tracing would be the preferred technique due to its ability to produce highly crisp and realistic graphics, if hardware were not a limitation. Making an immediate hardware transition from rasterization to ray tracing would have a severe impact on the computer graphics industry since it would require redevelopment of existing 3D graphics-employing software, so any transition to ray tracing would be gradual. Previous efforts to perform ray tracing on mainstream rasterizing hardware platforms with a single processor have performed poorly. This thesis explores how a multiple GPGPU system can be used to render scenes via ray tracing. A ray tracing engine and API groundwork was developed using NVIDIA’s CUDA (Compute Unified Device Architecture) GPGPU programming environment and was used to evaluate performance scalability across a multi-GPGPU system. This engine supports triangle, sphere, disc, rectangle, and torus rendering. It also allows independent activation of graphics features including procedural texturing, Phong illumination, reflections, translucency, and shadows. Correctness of rendered images validates the ray traced results, and timing of rendered scenes benchmarks performance. The main test scene contains all object types, has a total of 32 Abstract objects, and applies all graphics features. Ray tracing this scene using two GPGPUs outperformed the single-GPGPU and single-CPU systems, yielding respective speedups of up to 1.8 and 31.25. The results demonstrate how much potential exists in treating a modern dual-GPU architecture as a dual-GPGPU system in order to facilitate a transition from rasterization to ray tracing

Coordinating Changes in M-form and U-form Organizations

We introduce a method of modelling coordination inside an organization as a process of "attribute matching." Using this method, we compare organizational forms (U-form and M-form) in coordinating changes. In our model, organizational forms affect the information structure of an organization and thus the way to coordinate changes. Compared to the U-form, the M-form organization achieves better coordination but suffers from higher costs due to a lack of scale economies or a lack of what we call "attribute compatibility." The M-form has a distinctive advantage in carrying out experimentation which gives the organization more flexibility leading to more innovation and reform. We apply our theory to business firms, transition economies, and the organization of government (especially federalism). In the case of transition economies, our theory relates the initial conditions of organizational differences with reform strategies, especially the "big-bang" approach in Eastern Europe and the "experimental" approach in China.http://deepblue.lib.umich.edu/bitstream/2027.42/39668/3/wp284.pd

Triggering at High Luminosity Colliders

This article discusses the techniques used to select online promising events at high energy and high luminosity colliders. After a brief introduction, explaining some general aspects of triggering, the more specific implementation options for well established machines like the Tevatron and Large Hadron Collider are presented. An outlook on what difficulties need to be met is given when designing trigger systems at the Super Large Hadron Collider, or at the International Linear ColliderComment: Accepted for publication in New Journal of Physic

Exact Tests via Complete Enumeration: A Distributed Computing Approach

The analysis of categorical data often leads to the analysis of a contingency table. For large samples, asymptotic approximations are sufficient when calculating p-values, but for small samples the tests can be unreliable. In these situations an exact test should be considered. This bases the test on the exact distribution of the test statistic. Sampling techniques can be used to estimate the distribution. Alternatively, the distribution can be found by complete enumeration. A new algorithm is developed that enables a model to be defined by a model matrix, and all tables that satisfy the model are found. This provides a more efficient enumeration mechanism for complex models and extends the range of models that can be tested. The technique can lead to large calculations and a distributed version of the algorithm is developed that enables a number of machines to work efficiently on the same problem