Extending Knowledge Management to Mobile Workplaces

Knowledge and Knowledge Management (KM) are evolving into an increasingly eminent source of competitive advantage. However,for the time being, the potential of KM is usually limited to stationary workplaces. This excludes a multiplicity of mobile workers, many of them in charge of knowledge-intensive activities.This paper examines the capabilities and limitations of mobile technology usage in order to support KM. After a general overview of KM, the relevant mobile technology is introduced.Subsequently, the theory of mobile added values is employed to analyze the contributions of mobile technology for supporting KM in the different phases of the KM process. Especially the process of knowledge distribution is qualified to be supported through mobile technology.Knowledge Management; Mobile Commerce; Mobile Knowledge; Management; Mobile Business Processes; Mobile Added Values

Technology Options to Support the Implementation of Knowledge Management

Company is more aware that knowledge management is one of the important factors because it gives competitive advantages for them. Knowledge is intellectual asset that is owned by individual or company. Knowledge becomes very useful if it is documented or stored, organized, shared to others and can be understood and applied. Knowledge Management System (KMS) is made to manage knowledge. KMS does identifying process, capturing, organizing and disseminating knowledge. Technology is one of three model of KM that supports the implementation of KM. This time there are various options of technology that support the KM implementation for companies. In this research, there are various options or types of technology that can be used to support the implementation of knowledge management

Applications of social networking technology in IT-based knowledge management systems

This research enquires into how social networking technologies can help knowledge creation and sharing in IT-based knowledge management systems. Social networking technologies have changed the way people connect and collaborate allowing users to seek and find knowledge and expertise from both friends and strangers alike. Despite technology having been used in a variety of ways to support knowledge management systems, the use of social networking technology has been little explored. The famous SECI model highlights socialisation as an important aspect in transferring knowledge, yet IT-based knowledge management systems seem to miss out on this element. This research argues that combining knowledge management systems with social networking technology bridges this gap. Social software is becoming part of a commonplace set of tools available for organisations that may help IT-based knowledge management systems. Evidence is presented from a case study conducted in practice at an organisation. A mixture of qualitative and quantitative methods were used to collect the data and evaluate the effects of social networking technology within IT-based knowledge management systems. The research contributes towards the fields of knowledge management and knowledge management systems. The research inquiry found that the inclusion of social networking technology had positive effects on the IT-based knowledge management system and in turn the knowledge management initiative. The introduction of the IT-based knowledge management system, supported by social networking technology, resulted in a drastic improvement of 40.8% in the ease of finding knowledge and information, an increase by 30.4% in ease of sharing with other teams, and an improvement of 39.3% was also reported by employees feeling that the company tools support organisational growth. Data indicates an increase in other measurements of knowledge sharing and system metrics also show an increase in the usage, participation and contributions made in the IT-based knowledge management system supported by social networking technology. Building on the SECI model knowledge management theory is extended through the proposal of the social networking for knowledge management model (SN4KM) to support knowledge management systems designers

Knowledge management technology for integrated decision support systems in process industries

Premi extraordinari doctorat curs 2011-2012, àmbit d’Enginyeria IndustrialNowadays, factors such as globalization of trade, market uncertainty and fierce competition involve dwindling error margins in enterprises. Two key aspects for achieve it are the viability and the competitiveness of enterprises, which highly depend on the effectiveness for taking their decisions related to their manufacturing characteristics, such as economic efficiency, product quality, flexibility or reliability. For this reason, companies have taken the task, for many years, of develop better management information systems in order to help the decision makers to exploit data and models, with the final objective of discussing and improving decision-making. In this sense, decision support systems must be improved in order to deal with the large amount of available data and the heterogeneity of existing modeling approaches along the hierarchical levels in the enterprise structure. Hence, this thesis proposes the application of ontologies as a decision support tool, since they are increasingly seen as a key semantic technology for addressing heterogeneities and mitigating the problems they create and for enabling data mining by semantics-driven the knowledge processing. The aim of this thesis is to contribute to the development of decision support tools for the enterprise process industry. As a decision support tool, must be capable of become a robust model which interacts among the different decision hierarchical levels, providing a unified framework of data and information levels integration. On the other hand, this thesis also aims the improvement in the development of the ontologies. Firstly, a detailed state of the art about the different production process systems, knowledge management base on ontologies, as well as decision support systems is carried out. Based on this review, the specific thesis objectives are posed. Next, a methodology is proposed for the development and use of ontologies, based on the analysis and adaptation of previously existing methodologies. Such methodology is based on the improvement cycle (PSDA), allowing a better way to design, construct and apply domain ontologies. The second part of this thesis is devoted to the application of the different parts of the previously proposed methodology for the development of an ontological framework in the process industry domain concerning the strategic, tactical and operational decision levels. Next, the description of the decision areas in which the ontological framework is applied is presented. Namely, in the process control decision level, the coordination control is considered. Regarding scheduling decisions level, mathematical optimization approaches are applied. Finally, the distributed hierarchical decision level considers the mathematical optimization for decentralized supply chain networks is adopted. These decision areas and the performance of the proposed framework interaction are studied along the different case studies presented in the thesis. On the whole, this thesis represents a step forward toward the integration among the enterprise hierarchical levels, the process and enterprise standardization and improved procedures for decision-making. The aforementioned achievements are boosted by the application of semantic models, which are currently increasingly used.En la actualidad, factores como la globalización del comercio, la incertidumbre del mercado y la feroz competencia implican la disminución de los márgenes de error en las empresas. Dos aspectos claves para lograrlo son la viabilidad y la competitividad de las enterprisesm, que dependen en gran medida la eficacia para la toma de sus decisiones relacionadas con sus características de fabricación, tales como eficiencia económica, la calidad del producto, la flexibilidad y fiabilidad. Por esta razón, las empresas han dado a la tarea, desde hace muchos años, de desarrollar mejores sistemas de gestión de la información con el fin de ayudar a los tomadores de decisiones de explotación de datos y modelos, con el objetivo final de la discusión y mejorar la toma de decisiones. En este sentido, los sistemas de apoyo a las decisiones deben ser mejorados con el fin de hacer frente a la gran cantidad de datos disponibles y la heterogeneidad de los métodos de modelización existentes a lo largo de los niveles jerárquicos en la estructura de la empresa. Por lo tanto, esta tesis se propone la aplicación de ontologías como herramienta de apoyo a la decisión, ya que son cada vez más como una tecnología clave semántica para hacer frente a las heterogeneidades y la mitigación de los problemas que crean y para permitir la extracción de datos por la semántica impulsado la elaboración del conocimiento. El objetivo de esta tesis es contribuir al desarrollo de herramientas de apoyo para la industria de procesos empresariales. Como una herramienta de apoyo a la decisión, debe ser capaz de convertirse en un modelo sólido que interactúa entre los diferentes niveles de decisión jerárquica, proporcionando un marco unificado de datos e integración de los niveles de información. Por otra parte, esta tesis también tiene como objetivo la mejora en el desarrollo del área de ingeniería ontológica. En primer lugar, un estado detallado de la técnica sobre los diferentes sistemas de procesos de producción, la base de la gestión del conocimiento en ontologías, así como los sistemas de soporte de decisiones se ha llevado a cabo. Basado en esa revision, los objetivos específicos de la tesis se plantean. A continuación, se propone una metodología para el desarrollo y uso de ontologías, con base en el análisis y adaptación de las metodologías ya existentes. Dicha metodología se basa en el ciclo de mejora (PSDA), lo que permite una mejor manera de diseñar, construir y aplicar las ontologías de dominio. La segunda parte de esta tesis se dedica a la aplicación de las diferentes partes de la metodología propuesta anteriormente para el desarrollo de un marco ontológico en el ámbito de la industria de procesos relativos a los niveles de decisiones estratégicas, tácticas y operativas. A continuación, la descripción de las áreas de decisión en la que se aplica el marco ontológico se presenta. Es decir, en el nivel de decision de proceso de control, el control de la coordinación se considera. En cuanto al nivel de decisiones de programación de la producción, los métodos matemáticos de optimización se aplican. Finalmente, el nivel jerárquico distribuido decisión considera la optimización matemática de las redes descentralizadas de la cadena de suministro que se adopte. Estas áreas de decisión y el desempeño de la interacción marco propuesto se estudian a lo largo de los diferentes casos de estudio presentados en la tesis. En general, esta tesis supone un paso hacia adelante en la integración entre los niveles jerárquicos de la empresa, el proceso y la estandarización de la empresa y mejorar los procedimientos de toma de decisiones. Los logros mencionados se potencian mediante la aplicación de modelos semánticos, que actualmente se utilizan cada vez más.Award-winningPostprint (published version

An Evolution of Corporate Software Support Systems

This paper is a brief literature survey on Software Support Systems (SSSs) and Knowledge Management (KM). This paper aims to evaluate strategic decision making perspective where enterprise information and knowledge management plays a vital role. For this evaluation, Software Support Systems (SSSs) and Knowledge Management (KM) which helps in selecting different types of support systems and human factors that affect adoption of such computer based systems in organizations are reviewed. This paper helps to analyze different types of the software support systems and system adoption concepts for the enterprises. This paper also includes concepts related to the Knowledge Management, which helps organizations to learn. Organizations knowledge and the support systems help the enterprises to take strategic decisions. Concerned literature describes Software Support Systems (SSSs) as Corporate Portals (CPs), Decision Support Systems (DSSs), Group Decision Support Systems (GDSSs), Computerized Decision Support Systems, and Adaptive Decision Support System (ADSSs). In addition, Technology Acceptance Model (TAM) that analyzes factors which would affect peoples in the enterprises is included. The factors, such as individual perception, ease of use and usefulness are analyzed. Keywords: Software Support Systems, Knowledge Management, Technology Acceptance Models

APQL: A process-model query language

As business process management technology matures, organisations acquire more and more business process models. The management of the resulting collections of process models poses real challenges. One of these challenges concerns model retrieval where support should be provided for the formulation and efficient execution of business process model queries. As queries based on only structural information cannot deal with all querying requirements in practice, there should be support for queries that require knowledge of process model semantics. In this paper we formally define a process model query language that is based on semantic relationships between tasks in process models and is independent of any particular process modelling notation

Self-monitoring Practices, Attitudes, and Needs of Individuals with Bipolar Disorder: Implications for the Design of Technologies to Manage Mental Health

Objective To understand self-monitoring strategies used independently of clinical treatment by individuals with bipolar disorder (BD), in order to recommend technology design principles to support mental health management. Materials and Methods Participants with BD (N = 552) were recruited through the Depression and Bipolar Support Alliance, the International Bipolar Foundation, and WeSearchTogether.org to complete a survey of closed- and open-ended questions. In this study, we focus on descriptive results and qualitative analyses. Results Individuals reported primarily self-monitoring items related to their bipolar disorder (mood, sleep, finances, exercise, and social interactions), with an increasing trend towards the use of digital tracking methods observed. Most participants reported having positive experiences with technology-based tracking because it enables self-reflection and agency regarding health management and also enhances lines of communication with treatment teams. Reported challenges stem from poor usability or difficulty interpreting self-tracked data. Discussion Two major implications for technology-based self-monitoring emerged from our results. First, technologies can be designed to be more condition-oriented, intuitive, and proactive. Second, more automated forms of digital symptom tracking and intervention are desired, and our results suggest the feasibility of detecting and predicting emotional states from patterns of technology usage. However, we also uncovered tension points, namely that technology designed to support mental health can also be a disruptor. Conclusion This study provides increased understanding of self-monitoring practices, attitudes, and needs of individuals with bipolar disorder. This knowledge bears implications for clinical researchers and practitioners seeking insight into how individuals independently self-manage their condition as well as for researchers designing monitoring technologies to support mental health management

An Intelligent Interactive Knowledge Model for Decision Support in Real Time Traffic Management

This paper proposes the use of advanced knowledge models to support real time decision for management problems as an adequate response to the current needs and technology. The new conditions for human operation created by the telematics technology are discussed and a general architecture using knowledge modelling techniques is proposed. Then, the application of the approach to support real time management of the private traffic in the city of Turin is described