The impact of knowledge management processes on organisational performance

Copyright @ 2012 ISEing.In today's increasingly competitive business environment, the use of knowledge to gain a competitive advantage has become a serious concern for all organisations. However, despite the increasing number of studies relating to Knowledge Management (KM) in developed countries, few studies have explored this issue within the context of developing countries. Moreover, some industries have been affected more acutely than others in the transition to a knowledge-based economy. Towards covering this gap, this study aims at investigating the impact of Knowledge Management processes on Organisational Performance (OP). In this paper, the authors propose a conceptual model through an in-depth investigation of the previous and current studies in the area of Knowledge Management and Organisational Performance. Through an extensive classification of Knowledge Management processes, the proposed model explores the impact of each Knowledge Management process on improving the level of Organisational Performance. It is envisaged that this model can play a role in guiding the process of Knowledge Management implementation in order to maximise the beneficial effects of Knowledge Management processes on Organisational Performance

Measuring the Performance of Corporate Knowledge Management Systems

Whereas knowledge management systems (KMS) continues to gain popularity as a corporate most advanced information systems, the acceptance of standardized KMS assessment approaches has logged. Developing metrics to assess a corporate KMS is inherently problematic due to the intangible nature of knowledge-based resources, and for the fact that measurement is a precursor to improvement. This is true for knowledge management capabilities of an organization. Nonetheless, assessment is of vital importance for valuation purposes as well as to help managers determine whether particular KMS are effective working. The main focus of this paper is to explain the value of knowledge management and provide a general overview of measurement approaches. Finally, developing an improved measurement system for corporate KMS is considered the key to the competitive success of the organization.Corporate Knowledge, Knowledge Management Systems, Measuring the Performance

Operations research and computers

operational research

FROM DOCUMENT MANAGEMENT TO KNOWLEDGE MANAGEMENT

Documents circulating in paper form are increasingly being substituted by itselectronic equivalent in the modern office today so that any stored document can be retrievedwhenever needed later on. The office worker is already burdened with information overload, soeffective and effcient retrieval facilities become an important factor affecting worker productivity. The key thrust of this article is to analyse the benefits and importance of interaction betweendocument management and knowledge management. Information stored in text-based documentsrepresents a valuable repository for both the individual worker and the enterprise as a whole and ithas to be tapped into as part of the knowledge generation process.document management, knowledge management, Information and communication technologies

Applied business analytics approach to IT projects – Methodological framework

The design and implementation of a big data project differs from a typical business intelligence project that might be presented concurrently within the same organization. A big data initiative typically triggers a large scale IT project that is expected to deliver the desired outcomes. The industry has identified two major methodologies for running a data centric project, in particular SEMMA (Sample, Explore, Modify, Model and Assess) and CRISP-DM (Cross Industry Standard Process for Data Mining). More general, the professional organizations PMI (Project Management Institute) and IIBA (International Institute of Business Analysis) have defined their methods for project management and business analysis based on the best current industry practices. However, big data projects place new challenges that are not considered by the existing methodologies. The building of end-to-end big data analytical solution for optimization of the supply chain, pricing and promotion, product launch, shop potential and customer value is facing both business and technical challenges. The most common business challenges are unclear and/or poorly defined business cases; irrelevant data; poor data quality; overlooked data granularity; improper contextualization of data; unprepared or bad prepared data; non-meaningful results; lack of skill set. Some of the technical challenges are related to lag of resources and technology limitations; availability of data sources; storage difficulties; security issues; performance problems; little flexibility; and ineffective DevOps. This paper discusses an applied business analytics approach to IT projects and addresses the above-described aspects. The authors present their work on research and development of new methodological framework and analytical instruments applicable in both business endeavors, and educational initiatives, targeting big data. The proposed framework is based on proprietary methodology and advanced analytics tools. It is focused on the development and the implementation of practical solutions for project managers, business analysts, IT practitioners and Business/Data Analytics students. Under discussion are also the necessary skills and knowledge for the successful big data business analyst, and some of the main organizational and operational aspects of the big data projects, including the continuous model deployment

Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)

Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐ FEDERJA‐148)” and The APC was funded by the same research gran

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version