The role of a firm's absorptive capacity and the technology transfer process in clusters: How effective are technology centres in low-tech clusters?

This paper analyses how the internal resources of small- and medium-sized enterprises determine access (learning processes) to technology centres (TCs) or industrial research institutes (innovation infrastructure) in traditional low-tech clusters. These interactions basically represent traded (market-based) transactions, which constitute important sources of knowledge in clusters. The paper addresses the role of TCs in low-tech clusters, and uses semi-structured interviews with 80 firms in a manufacturing cluster. The results point out that producer–user interactions are the most frequent; thus, the higher the sector knowledge-intensive base, the more likely the utilization of the available research infrastructure becomes. Conversely, the sectors with less knowledge-intensive structures, i.e. less absorptive capacity (AC), present weak linkages to TCs, as they frequently prefer to interact with suppliers, who act as transceivers of knowledge. Therefore, not all the firms in a cluster can fully exploit the available research infrastructure, and their AC moderates this engagement. In addition, the existence of TCs is not sufficient since the active role of a firm's search strategies to undertake interactions and conduct openness to available sources of knowledge is also needed. The study has implications for policymakers and academia.

A visual framework to accelerate knowledge discovery based on dimensionality reduction minimizing degradation of quality

Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

Using Knowledge Modelling Tools for Agent-Based Systems: The Experience of KSM

The aim of this chapter is to discuss the applicability of recently proposed knowledge modelling tools to the development of agent-based systems. The discussion is derived from the real world experience of a particular software tool called KSM (Knowledge Structure Manager). The chapter provides details about this tool and then proceeds to show in which forms the software may be used to support the development of agent-based systems. Two multiagent systems, one in the field of telecommunications management and the other one in the field of flood control, are described. Conclusions about these studies are presented, summarizing the main contributions that knowledge modelling tools can bring to the development of agent-based systems.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

KATS: A Knowledge Acquisition Tool Based on Electronic Document Processing

This paper describes a particular knowledge acquisition tool for the construction and maintenance of the knowledge model of an intelligent system for emergency management in the field of hydrology. This tool has been developed following an innovative approach directed to end-users non familiarized in computer oriented terminology. According to this approach, the tool is conceived as a document processor specialized in a particular domain (hydrology) in such a way that the whole knowledge model is viewed by the user as an electronic document. The paper first describes the characteristics of the knowledge model of the intelligent system and summarizes the problems that we found during the development and maintenance of such type of model. Then, the paper describes the KATS tool, a software application that we have designed to help in this task to be used by users who are not experts in computer programming. Finally, the paper shows a comparison between KATS and other approaches for knowledge acquisition.

Enhancing Evacuation Plans with a Situation Awareness System Based on End-User Knowledge Provision.

Recent disasters have shown that having clearly defined preventive procedures and decisions is a critical component that minimizes evacuation hazards and ensures a rapid and successful evolution of evacuation plans. In this context, we present our Situation-Aware System for enhancing Evacuation Plans (SASEP) system, which allows creating end-user business rules that technically support the specific events, conditions and actions related to evacuation plans. An experimental validation was carried out where 32 people faced a simulated emergency situation, 16 of them using SASEP and the other 16 using a legacy system based on static signs. From the results obtained, we compare both techniques and discuss in which situations SASEP offers a better evacuation route option, confirming that it is highly valuable when there is a threat in the evacuation route. In addition, a study about user satisfaction using both systems is presented showing in which cases the systems are assessed as satisfactory, relevant and not frustrating.

Portfolio Entrepreneurship in Family Firms: A Resource-based Perspective

The phenomenon of portfolio entrepreneurship has attracted considerable scholarly attention and is particularly relevant in the family fi rm context. However, there is a lack of knowledge of the process through which portfolio entrepreneurship develops in family firms. We address this gap by analyzing four in-depth, longitudinal family firm case studies from Europe and Latin America. Using a resource-based perspective, we identify six distinct resource categories that are relevant to the portfolio entrepreneurship process. Furthermore, we reveal that their importance varies across time. Our resulting resource-based process model of portfolio entrepreneurship in family firms makes valuable contributions to both theory and practice.

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The volumes are issued in two parts each, with individual t.-p.

The new Schaff-herzog encyclopedia of religious knowledge, embracing Biblical, historical, doctrinal, and practical theology, and Biblical, theological, and Biblical, theological, and ecclesiastical biography from the earliest times to the present day; based on the 3d ed. of the Realencyklopädie founded by J. J. Herzog,

Mode of access: Internet.

Electronic commerce investments, the resource-based view of the firm, and firm market value

Firms have embraced electronic commerce as a means of doing business, either because they see it as a way to improve efficiency, grow market share, expand into new markets, or because they view it as essential for survival. Recent research in the United States provides some evidence that the market does value investments in electronic commerce. Following research that suggests that, in certain circumstances, the market values noninnovative investments as well as innovative investments in new products, we partition electronic commerce investment project announcements into innovative and noninnovative to determine whether there are excess returns associated with these types of announcements. Apart from our overall results being consistent with the United States findings that the market values investments in electronic commerce projects, we also find that noninnovative investments are perceived as more valuable to the firm than innovative investments. On average, the market expects innovative investments to earn a return commensurate with their risk. We conclude that innovative electronic commerce projects are most likely seen by the capital market as easily replicable, and consequently have little, if any, competitive advantage period. On the other hand, we conclude from the noninnovative investment results that these types of investments are seen as being compatible with a firm's assets-in-place, in particular, its information technology capabilities, a view consistent with the resource-based view of the firm.

A community-based wildlife survey: the knowledge and attitudes of residents of suburban Brisbane, with a focus on bandicoots

Within the expanding city of Brisbane in south-east Queensland, numerous fragments of native and regrowth vegetation are scattered across the largely urbanised landscape. These fragments provide refuge to a great diversity of native wildlife, and, provide residents with the opportunity to experience nature on their doorstep. To assess the diversity and abundance of this wildlife, recent changes in these parameters, and the value of wildlife and bushland fragments to residents of Brisbane, a questionnaire survey was distributed to 300 households each located adjacent to one of 38 urban bushland fragments. A total of 172 surveys (57%) were returned, producing 768 records of 83 fauna species, dominated by birds and mammals; bandicoots were widely reported from the 38 fragments. Several historical records provided evidence of recent local extinctions within fragments, highlighting the continuing declines in various species of native wildlife within Brisbane. Several human-wildlife conflicts were identified, but overall residents were tolerant of such conflicts. Bandicoots were disliked by a small minority (3%) of residents owing to the holes they dig in lawns and gardens in search of food. and their potential as vectors of ticks. Most respondents expressed ail appreciation for the presence of native wildlife (96%) and bushland fragments (97%) in their local area, emphasising the importance of incorporating human dimension values into the management of this urban biodiversity.

Examining the role of networking capability in small and medium firm internationalization

While research on SME internationalization has increased, there remains a lack of relevant theory on the SME internationalization process. The literature reports that small firms overcome their resource poverty-based constraints to internationalization by developing network relationships. Networking enables SMEs to acquire much needed internationalization process knowledge, and knowledge for the development of innovative products and services for this internationalization. However, networking activity has not yet been conceptualized and measured as a competitive capability in internationalization research. Drawing on the capability-based theory of competitive strategy, this paper conjectures that internationally entrepreneurial SMEs build and nurture distinctive networking capabilities, enabling them to acquire new knowledge. These learning capabilities enable them to pursue innovation thereby facilitating nternationalization. Data from Australian firms largely supports the conceptual framework. Implications for theory and practice are presented.