237,929 research outputs found

    CoPs-Centered Knowledge Management

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    Rajiv Khosla is an Associate Professor at School of Business, La Trobe University. He is the director of externally funded Business Intelligence Institute-Business Systems and Knowledge Modelling research laboratory. Rajiv has a multi-disciplinary background in management, engineering and computer science. He has published over 120 refereed journal and conference papers. He has also authored four books (research monographs) in the area of Emotional Intelligence, Human-Centred e-Business, Multimedia based Socio-technical Information systems, Intelligent Hybrid Multi-agent Systems. Rajiv is the Associate editor of the International Journal of Pattern Recognition, Regional editor of Journal of Intelligent Manufacturing (Springer-verlag), and Action Editor of Journal of Cognitive Systems Research. He has been a project leader of over a dozen industry projects and has commercialised four IT products in Australia. Associate Professor Rajiv Khosla Business Intelligence Institute and Business Systems Knowledge Modeling Laboratory (http://www.latrobe.edu.au/bskm) School of Business, La Trobe University, Melbourne, Victoria – 3086, Australia E-Mail: [email protected] of the primary reasons identified for the failure of existing knowledge management solutions has been that knowledge management tools and research have primarily been designed around technology push-models as against strategy pull-models. In an era where organizations are undergoing rapid and discontinuous change it is imperative that knowledge management systems and organizational entities like CoPs that facilitate knowledge management and organizational transformation are more closely aligned with business strategies and goals of an organization. This would enable organizations to respond more quickly to changing business environments and corresponding change in their knowledge management needs from time to time. This seminar presents a strategy-pull approach for Modeling and Design of CoPs-centered Knowledge Management Systems to facilitate organizational transformation. Among other aspects the seminar will focus on definition of dimensions and criteria for defining CoPs in an organization, application of fuzzy integral techniques to rank 16 criteria employed by CoPs to engage in knowledge management. From a knowledge management and organizational transformation perspective this approach will enable a more direct relationship between business strategy, CoPs and Knowledge Management solutions.published_or_final_versionCentre for Information Technology in Education, University of Hong Kon

    Two-Stage Memory Allocation using AHP & Knapsack at PT Berca Hardayaperkasa

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    We propose to manage a (MicroStrategy) Business Intelligence Server in terms of RAM allocation for its Intelligent Cubes as a two-stage resource allocation problem in which the first stage is formulated as an multi-criteria problem that can be solved using Analytic Hierarchy Process (AHP) and the second stage is multiple (several) 0-1 classic Knapsack problems with the constraints that are obtained using the result from the first stage. This Approach happens to have an advantage in terms of computational complexity as well, it reduces from O(nM) to O(max{nj}max{Mj}) when calculated in parallel. We illustrate our proposal with a numerical example based on our experience

    Human Resource Management and Artificial Intelligence: A Bibliometric Exploration

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    The concept of artificial intelligence, a driving force behind human resource management, has recently gained popularity in the academic community. This study explores the intellectual structure of this field using the Scopus database in the subject area of business, management and accounting. Bibliographic analysis, a recent and rigorous method for delving into scientific data, is used in this investigation. The approach used is a structured and transparent process divided into four steps: (1) search criteria; (2) selection of database and documents; (3) selection of software and data pre-processing; and (4) analysis of findings. We employ bibliometric mapping to observe their numerous linkages and performance evaluation to learn about their structure. A total of 67 articles were collected from the Scopus database between 2015 and 2022 using certain keywords (artificial intelligence, expert systems, big data analytics, and human resource management) and some specific filters (subject–business, management and accounting; language-English; document–article, review articles and source-journals). Ten research clusters were identified: Cluster 1: multi-agent system; Cluster 2: decision support system; Cluster 3: internet of things; Cluster 4: active learning; Cluster 5: decision tree; Cluster 6: optimisation; Cluster 7: software design; Cluster 8: data mining; Cluster 9: cloud computing; Cluster 10: human-robot interaction. The findings could be helpful for researchers and practitioners in the HRM field to extend their knowledge and understanding of AI and HRM research. This study can provide notable guidance and future directions for quite a few firms in expanding the use of AI in HRM. Keywords: Artificial intelligence, human resource management, bibliometric analysi

    Agile Requirements Engineering: A systematic literature review

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    Nowadays, Agile Software Development (ASD) is used to cope with increasing complexity in system development. Hybrid development models, with the integration of User-Centered Design (UCD), are applied with the aim to deliver competitive products with a suitable User Experience (UX). Therefore, stakeholder and user involvement during Requirements Engineering (RE) are essential in order to establish a collaborative environment with constant feedback loops. The aim of this study is to capture the current state of the art of the literature related to Agile RE with focus on stakeholder and user involvement. In particular, we investigate what approaches exist to involve stakeholder in the process, which methodologies are commonly used to present the user perspective and how requirements management is been carried out. We conduct a Systematic Literature Review (SLR) with an extensive quality assessment of the included studies. We identified 27 relevant papers. After analyzing them in detail, we derive deep insights to the following aspects of Agile RE: stakeholder and user involvement, data gathering, user perspective, integrated methodologies, shared understanding, artifacts, documentation and Non-Functional Requirements (NFR). Agile RE is a complex research field with cross-functional influences. This study will contribute to the software development body of knowledge by assessing the involvement of stakeholder and user in Agile RE, providing methodologies that make ASD more human-centric and giving an overview of requirements management in ASD.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2015-71938-RED

    A model to assess customer alignment through customer experience concepts

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    Business and Information Technology Alignment (BITA) has been one of the main concerns of IT and Business executives and directors due to its importance to overall company performance, especially today in the age of digital transformation. For BITA has been developed several models which in general has focused in the implementation of alignment strategies for the internal operation of the organizations and in the measurement of this internal alignment, but, there is still a big gap in measurement models of the alignment with the external environment of the organizations. In this paper is presented the design and application of a maturity measurement model for BITA with the customers, where the customers are actors of the external environment of the companies. The proposed model involves evaluation criteria and business practices which the companies ideally do for improve the relationship with their customers.Comment: 12 pages, Preprint version, BIS 2019 International Workshops, Seville, Spain, June 26 to 28, 2019, Revised Paper

    Multi crteria decision making and its applications : a literature review

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    This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM
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