883 resultados para Knowledge organization systems
Knowledge management for enterprise systems: observations from small, medium and large organizations
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Anecdotal evidence suggests that the lifecycle-wide management of Enterprise System (ES) related knowledge is critical for ES health and longevity. At a time where many ES-vendors now offering solutions to Small and Medium size organizations, this paper investigates the ability of Small and Medium size organizations to maintain a lifecycle-wide knowledge management strategy. The paper explores the alleged differences in the knowledge management practices across 27 small, medium and large organizations that had implemented a market-leading ES. Results suggest that: (1) despite similar knowledge creation efforts in all three organizational sizes, small organizations struggle with retaining, transferring and applying the knowledge. The study also reveals that, (2) the overall goodness of the knowledge management process in larger organizations remains higher than their small and medium counterparts.
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Both Knowledge Management (KM) and Project Management (PM) are known as crucial factors to develop competitive advantage(CA). PM Office (PMO) is recognized as a strong solution to institutionalize PM practices in organization. However, according to the literature there is a significant gap in addressing KM practices in the PMO. In other words, existing PMO maturity models has not been addressed from KM perceptive. This paper discusses undertaken investigations of both KM and PM as an initial part of PhD research on the role of knowledge in PMO
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Niklas Luhmann's theory of social systems has been widely influential in the German-speaking countries in the past few decades. However, despite its significance, particularly for organization studies, it is only very recently that Luhmann's work has attracted attention on the international stage as well. This Special Issue is in response to that. In this introductory paper, we provide a systematic overview of Luhmann's theory. Reading his work as a theory about distinction generating and processing systems, we especially highlight the following aspects: (i) Organizations are processes that come into being by permanently constructing and reconstructing themselves by means of using distinctions, which mark what is part of their realm and what not. (ii) Such an organizational process belongs to a social sphere sui generis possessing its own logic, which cannot be traced back to human actors or subjects. (iii) Organizations are a specific kind of social process characterized by a specific kind of distinction: decision, which makes up what is specifically organizational about organizations as social phenomena. We conclude by introducing the papers in this Special Issue. Copyright © 2006 SAGE.
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Companies face the challenges of expanding their markets, improving products, services and processes, and exploiting intellectual capital in a dynamic network. Therefore, more companies are turning to an Enterprise System (ES). Knowledge management (KM) has also received considerable attention and is continuously gaining the interest of industry, enterprises, and academia. For ES, KM can provide support across the entire lifecycle, from selection and implementation to use. In addition, it is also recognised that an ontology is an appropriate methodology to accomplish a common consensus of communication, as well as to support a diversity of KM activities, such as knowledge repository, retrieval, sharing, and dissemination. This paper examines the role of ontology-based KM for ES (OKES) and investigates the possible integration of ontology-based KM and ES. The authors develop a taxonomy as a framework for understanding OKES research. In order to achieve the objective of this study, a systematic review of existing research was conducted. Based on a theoretical framework of the ES lifecycle, KM, KM for ES, ontology, and ontology-based KM, guided by the framework of study, a taxonomy for OKES is established.
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Nowadays, Workflow Management Systems (WfMSs) and, more generally, Process Management Systems (PMPs) are process-aware Information Systems (PAISs), are widely used to support many human organizational activities, ranging from well-understood, relatively stable and structures processes (supply chain management, postal delivery tracking, etc.) to processes that are more complicated, less structured and may exhibit a high degree of variation (health-care, emergency management, etc.). Every aspect of a business process involves a certain amount of knowledge which may be complex depending on the domain of interest. The adequate representation of this knowledge is determined by the modeling language used. Some processes behave in a way that is well understood, predictable and repeatable: the tasks are clearly delineated and the control flow is straightforward. Recent discussions, however, illustrate the increasing demand for solutions for knowledge-intensive processes, where these characteristics are less applicable. The actors involved in the conduct of a knowledge-intensive process have to deal with a high degree of uncertainty. Tasks may be hard to perform and the order in which they need to be performed may be highly variable. Modeling knowledge-intensive processes can be complex as it may be hard to capture at design-time what knowledge is available at run-time. In realistic environments, for example, actors lack important knowledge at execution time or this knowledge can become obsolete as the process progresses. Even if each actor (at some point) has perfect knowledge of the world, it may not be certain of its beliefs at later points in time, since tasks by other actors may change the world without those changes being perceived. Typically, a knowledge-intensive process cannot be adequately modeled by classical, state of the art process/workflow modeling approaches. In some respect there is a lack of maturity when it comes to capturing the semantic aspects involved, both in terms of reasoning about them. The main focus of the 1st International Workshop on Knowledge-intensive Business processes (KiBP 2012) was investigating how techniques from different fields, such as Artificial Intelligence (AI), Knowledge Representation (KR), Business Process Management (BPM), Service Oriented Computing (SOC), etc., can be combined with the aim of improving the modeling and the enactment phases of a knowledge-intensive process. The 1st International Workshop on Knowledge-intensive Business process (KiBP 2012) was held as part of the program of the 2012 Knowledge Representation & Reasoning International Conference (KR 2012) in Rome, Italy, in June 2012. The workshop was hosted by the Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti of Sapienza Universita di Roma, with financial support of the University, through grant 2010-C26A107CN9 TESTMED, and the EU Commission through the projects FP7-25888 Greener Buildings and FP7-257899 Smart Vortex. This volume contains the 5 papers accepted and presented at the workshop. Each paper was reviewed by three members of the internationally renowned Program Committee. In addition, a further paper was invted for inclusion in the workshop proceedings and for presentation at the workshop. There were two keynote talks, one by Marlon Dumas (Institute of Computer Science, University of Tartu, Estonia) on "Integrated Data and Process Management: Finally?" and the other by Yves Lesperance (Department of Computer Science and Engineering, York University, Canada) on "A Logic-Based Approach to Business Processes Customization" completed the scientific program. We would like to thank all the Program Committee members for the valuable work in selecting the papers, Andrea Marrella for his valuable work as publication and publicity chair of the workshop, and Carola Aiello and the consulting agency Consulta Umbria for the organization of this successful event.
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Management scholars and practitioners emphasize the importance of the size and diversity of a knowledge worker's social network. Constraints on knowledge workers’ time and energy suggest that more is not always better. Further, why and how larger networks contribute to valuable outcomes deserves further understanding. In this study, we offer hypotheses to shed insight on the question of the diminishing returns of large networks and the specific form of network diversity that may contribute to innovative performance among knowledge workers. We tested our hypotheses using data collected from 93 R&D engineers in a Sino-German automobile electronics company located in China. Study findings identified an inflection point, confirming our hypothesis that the size of the knowledge worker's egocentric network has an inverted U-shaped effect on job performance. We further demonstrate that network dispersion richness (the number of cohorts that the focal employee has connections to) rather than network dispersion evenness (equal distribution of ties across the cohorts) has more influence on the knowledge worker's job performance. Additionally, we found that the curvilinear effect of network size is fully mediated by network dispersion richness. Implications for future research on social networks in China and Western contexts are discussed.
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This paper presents the results from a study of information behaviors, with specific focus on information organisation-related behaviours conducted as part of a larger daily diary study with 34 participants. The findings indicate that organization of information in everyday life is a problematic area due to various factors. The self-evident one is the inter-subjectivity between the person who may have organized the information and the person looking for that same information (Berlin et. al., 1993). Increasingly though, we are not just looking for information within collections that have been designed by someone else, but within our own personal collections of information, which frequently include books, electronic files, photos, records, documents, desktops, web bookmarks, and portable devices. The passage of time between when we categorized or classified the information, and the time when we look for the same information, poses several problems of intra-subjectivity, or the difference between our own past and present perceptions of the same information. Information searching, and hence the retrieval of information from one's own collection of information in everyday life involved a spatial and temporal coordination with one's own past selves in a sort of cognitive and affective time travel, just as organizing information is a form of anticipatory coordination with one's future information needs. This has implications for finding information and also on personal information management.
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Induction is an interesting model of legal reasoning, since it provides a method of capturing initial states of legal principles and rules, and adjusting these principles and rules over time as the law changes. In this article I explain how Artificial Intelligence-based inductive learning algorithms work, and show how they have been used in law to model legal domains. I identify some problems with implementations undertaken in law to date, and create a taxonomy of appropriate cases to use in legal inductive inferencing systems. I suggest that inductive learning algorithms have potential in modeling law, but that the artificial intelligence implementations to date are problematic. I argue that induction should be further investigated, since it has the potential to be an extremely useful mechanism for understanding legal domains.
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Recent literature on Enterprise System (ES) implementation projects highlights the importance of Knowledge Integration (KI) for implementation success. The fundamental characteristics of ES - integration of modules, business process view, and aspects of information transparency - necessitate that all frequent end-users share a reasonable amount of common knowledge and integrate their knowledge to yield new knowledge. Unfortunately, the importance of KI is often overlooked and little about the role of KI in ES success is known. In this chapter, the authors study the KI impact on ES success that is relevant to the ES post-implementation in support of organizations' returns on their ES investments. They adopt the ES post-implementation segment of ES utilization to explore whether the KI approach is causally linked to ES success. The research model was tested in a multi-industry sample in Malaysia from which data was gathered from managerial and operational employees spread across six large organizations. Consistent with the explanation by knowledge-based theory, the results show that KI was valid and significantly related to the outcome of ES that relates to an organization's performance, which the authors refer to as ES success. The KI positive impact on the success of ES drives one to highlight the importance of ontological KI in the complexity of the ES environment. The authors believe that focusing on an ontology through the KI perspective can make significant contributions to current ES problems.
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Semantic knowledge is supported by a widely distributed neuronal network, with differential patterns of activation depending upon experimental stimulus or task demands. Despite a wide body of knowledge on semantic object processing from the visual modality, the response of this semantic network to environmental sounds remains relatively unknown. Here, we used fMRI to investigate how access to different conceptual attributes from environmental sound input modulates this semantic network. Using a range of living and manmade sounds, we scanned participants whilst they carried out an object attribute verification task. Specifically, we tested visual perceptual, encyclopedic, and categorical attributes about living and manmade objects relative to a high-level auditory perceptual baseline to investigate the differential patterns of response to these contrasting types of object-related attributes, whilst keeping stimulus input constant across conditions. Within the bilateral distributed network engaged for processing environmental sounds across all conditions, we report here a highly significant dissociation within the left hemisphere between the processing of visual perceptual and encyclopedic attributes of objects.
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An overview of dynamic self-organization phenomena in complex ionized gas systems, associated physical phenomena, and industrial applications is presented. The most recent experimental, theoretical, and modeling efforts to understand the growth mechanisms and dynamics of nano- and micron-sized particles, as well as the unique properties of the plasma-particle systems (colloidal, or complex plasmas) and the associated physical phenomena are reviewed and the major technological applications of micro- and nanoparticles are discussed. Until recently, such particles were considered mostly as a potential hazard for the microelectronic manufacturing and significant efforts were applied to remove them from the processing volume or suppress the gas-phase coagulation. Nowadays, fine clusters and particulates find numerous challenging applications in fundamental science as well as in nanotechnology and other leading high-tech industries.
Resumo:
Niklas Luhmann's theory of social systems has been widely influential in the German-speaking countries in the past few decades. However, despite its significance, particularly for organization studies, it is only very recently that Luhmann's work has attracted attention on the international stage as well. This Special Issue is in response to that. In this introductory paper, we provide a systematic overview of Luhmann's theory. Reading his work as a theory about distinction generating and processing systems, we especially highlight the following aspects: (i) Organizations are processes that come into being by permanently constructing and reconstructing themselves by means of using distinctions, which mark what is part of their realm and what not. (ii) Such an organizational process belongs to a social sphere sui generis possessing its own logic, which cannot be traced back to human actors or subjects. (iii) Organizations are a specific kind of social process characterized by a specific kind of distinction: decision, which makes up what is specifically organizational about organizations as social phenomena. We conclude by introducing the papers in this Special Issue. Copyright © 2006 SAGE.
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Background & Research Focus Managing knowledge for innovation and organisational benefit has been extensively investigated in studies of large firms (Smith, Collins & Clark, 2005; Zucker, et al., 2007) and to a large extent there is limited research into studies of small- and medium- sized enterprises (SMEs). There are some investigations in knowledge management research on SMEs, but what remains to be seen in particular is the question of where are the potential challenges for managing knowledge more effectively within these firms? Effective knowledge management (KM) processes and systems lead to improved performance in pursuing distinct capabilities that contribute to firm-level innovation (Nassim 2009; Zucker et al. 2007; Verona and Ravasi 2003). Managing internal and external knowledge in a way that links it closely to the innovation process can assist the creation and implementation of new products and services. KM is particularly important in knowledge intensive firms where the knowledge requirements are highly specialized, diverse and often emergent. However, to a large extent the KM processes of small firms that are often the source of new knowledge and an important element of the value networks of larger companies have not been closely studied. To address this gap which is of increasing importance with the growing number of small firms, we need to further investigate knowledge management processes and the ways that firms find, capture, apply and integrate knowledge from multiple sources for their innovation process. This study builds on the previous literature and applies existing frameworks and takes the process and activity view of knowledge management as a starting point of departure (see among others Kraaijenbrink, Wijnhoven & Groen, 2007; Enberg, Lindkvist, & Tell, 2006; Lu, Wang & Mao, 2007). In this paper, it is attempted to develop a better understanding of the challenges of knowledge management within the innovation process in small knowledge-oriented firms. The paper aims to explore knowledge management processes and practices in firms that are engaged in the new product/service development programs. Consistent with the exploratory character of the study, the research question is: How is knowledge integrated, sourced and recombined from internal and external sources for innovation and new product development? Research Method The research took an exploratory case study approach and developed a theoretical framework to investigate the knowledge situation of knowledge-intensive firms. Equipped with the conceptual foundation, the research adopted a multiple case study method investigating four diverse Australian knowledge-intensive firms from IT, biotechnology, nanotechnology and biochemistry industries. The multiple case study method allowed us to document in some depth the knowledge management experience of the theses firms. Case study data were collected through a review of company published data and semi-structured interviews with managers using an interview guide to ensure uniform coverage of the research themes. This interview guide was developed following development of the framework and a review of the methodologies and issues covered by similar studies in other countries and used some questions common to these studies. It was framed to gather data around knowledge management activity within the business, focusing on the identification, acquisition and utilisation of knowledge, but collecting a range of information about subject as well. The focus of the case studies was on the use of external and internal knowledge to support their knowledge intensive products and services. Key Findings Firstly a conceptual and strategic knowledge management framework has been developed. The knowledge determinants are related to the nature of knowledge, organisational context, and mechanism of the linkages between internal and external knowledge. Overall, a number of key observations derived from this study, which demonstrated the challenges of managing knowledge and how important KM is as a management tool for innovation process in knowledge-oriented firms. To summarise, findings suggest that knowledge management process in these firms is very much project focused and not embedded within the overall organisational routines and mainly based on ad hoc and informal processes. Our findings highlighted lack of formal knowledge management process within our sampled firms. This point to the need for more specialised capabilities in knowledge management for these firms. We observed a need for an effective knowledge transfer support system which is required to facilitate knowledge sharing and particularly capturing and transferring tacit knowledge from one team members to another. In sum, our findings indicate that building effective and adaptive IT systems to manage and share knowledge in the firm is one of the biggest challenges for these small firms. Also, there is little explicit strategy in small knowledge-intensive firms that is targeted at systematic KM either at the strategic or operational level. Therefore, a strategic approach to managing knowledge for innovation as well as leadership and management are essential to achieving effective KM. In particular, research findings demonstrate that gathering tacit knowledge, internal and external to the organization, and applying processes to ensure the availability of knowledge for innovation teams, drives down the risks and cost of innovation. KM activities and tools, such as KM systems, environmental scanning, benchmarking, intranets, firm-wide databases and communities of practice to acquire knowledge and to make it accessible, were elements of KM. Practical Implications The case study method that used in this study provides practical insight into the knowledge management process within Australian knowledge-intensive firms. It also provides useful lessons which can be used by other firms in managing the knowledge more effectively in the innovation process. The findings would be helpful for small firms that may be searching for a practical method for managing and integrating their specialised knowledge. Using the results of this exploratory study and to address the challenges of knowledge management, this study proposes five practices that are discussed in the paper for managing knowledge more efficiently to improve innovation: (1) Knowledge-based firms must be strategic in knowledge management processes for innovation, (2) Leadership and management should encourage various practices for knowledge management, (3) Capturing and sharing tacit knowledge is critical and should be managed, (4)Team knowledge integration practices should be developed, (5) Knowledge management and integration through communication networks, and technology systems should be encouraged and strengthen. In sum, the main managerial contribution of the paper is the recognition of knowledge determinants and processes, and their effects on the effective knowledge management within firm. This may serve as a useful benchmark in the strategic planning of the firm as it utilises new and specialised knowledge.
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Knowledge Management (KM) is vital factor to successfully undertake projects. The temporary nature of projects necessitates employing useful KM practices for tackling issues such as knowledge leakiness and rework. The Project Management Office (PMO) is a unit within organizations to facilitate and oversee organizational projects. Project Management Maturity Models (PMMM) shows the development of PMOs from immature to mature levels. The existing PMMMs have focused on discussing Project Management (PM) practices, however, the management of project knowledge is yet to be addressed, at various levels of maturity. This research project was undertaken to investigate the mentioned gap for addressing KM practices at the existing PMMMs. Due to the exploratory and inductive nature of this research, qualitative methods were chosen as the research methodology. In total, three cases selected from different industries: research; mining and government organizations, to provide broad categories for research and research questions were examined using the developed framework. This paper presents the partial findings of undertaken investigation of the research organisation with the lowest level of maturity. The result shows that knowledge creation and capturing are the most important processes, while knowledge transferring and reusing are not as important as the other two processes. In addition, it was revealed that provision of “knowledge about client” and “project management knowledge” are the most important types of knowledge that are required at this level of maturity. In conclusion, the outcomes of this paper shall provide powerful guidance to PMOs at lowest level of maturity from KM point of view.