54,371 research outputs found

    Competitive Intelligence Practices in Small Business: a Social Media Analytics Approach

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    With the recent advances in the development of Information and Communication Technologies (ICTs), a lot of small businesses and micro-enterprises achieve their business goals and reach economic development. While Competitive Intelligence (CI) is the practice of studying competitors and competitive environment, its purpose is to provide actionable intelligence for informative organizational decision making. In this study, we propose a social media analytics approach to understand the CI of the small businesses and micro-enterprises. Three research questions are proposed to further guide the future research. Based on Chen (1996)’s framework, case study will be conducted from micro-enterprises. The work contributes to the CI body of knowledge by introducing advanced text mining techniques and social mediate data into CI analysis in the context of small businesses. Evaluation experiment will be conducted in the future

    Who needs XAI in the Energy Sector? A Framework to Upgrade Black Box Explainability

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    Artificial Intelligence (AI)-based methods in the energy sector challenge companies, organizations, and societies. Organizational issues include traceability, certifiability, explainability, responsibility, and efficiency. Societal challenges include ethical norms, bias, discrimination, privacy, and information security. Explainable Artificial Intelligence (XAI) can address these issues in various application areas of the energy sector, e.g., power generation forecasting, load management, and network security operations. We derive Key Topics (KTs) and Design Requirements (DRs) and develop Design Principles (DPs) for efficient XAI applications through Design Science Research (DSR). We analyze 179 scientific articles to identify our 8 KTs for XAI implementation through text mining and topic modeling. Based on the KTs, we derive 15 DRs and develop 18 DPs. After that, we discuss and evaluate our results and findings through expert surveys. We develop a Three-Forces Model as a framework for implementing efficient XAI solutions. We provide recommendations and a further research agenda

    Towards the integration of enterprise software: The business manufacturing intelligence

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    Nowadays, the Information Communication Technology has pervaded literally the companies. In the company circulates an huge amount of information but too much information doesn’t provide any added value. The overload of information exceeds individual processing capacity and slowdowns decision making operations. We must transform the enormous quantity of information in useful knowledge taking in consideration that information becomes obsolete quickly in condition of dynamic market. Companies process this information by specific software for managing, efficiently and effectively, the business processes. In this paper we analyse the myriad of acronyms of software that is used in enterprises with the changes that occurred over the time, from production to decision making until to convergence in an intelligent modular enterprise software, that we named Business Manufacturing Intelligence (BMI), that will manage and support the enterprise in the futurebusiness manufacturing intelligence, enterprise resource planning; business intelligence; management software; automation software; decision making software

    THE KNOWLEDGE MANAGEMENT – NECESSITY FOR THE MODERNIZATION OF THE ORGANIZATIONS

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    If individuals and technologies can harmonize their intelligence under various forms, only the intelligent organizations will have the capacity to transform and coordinate these abilities for their own advantage by using informational technologies, by combining the most advanced software technologies with the newest management instruments in order to produce extremely efficient organizations. The information excess is a chronic phenomenon for the modern organization, so that the lack of the capacity to filter and use relevant information is a consequence of the inefficiency to manage the knowledge fund, of the lack of a clear strategy with a common purpose for personnel and team. Today, almost the intelligent organizations must manage and apply the entire knowledge fund, they must use instruments and technologies in order to build an informational architecture, having as a purpose the competitiveness in a turbulent and changing environment. The apportion of the information and knowledge of the organization, the exchange of information between employees, departments and even other companies are facilitated by the information and communication technology. Not all information are valuable, but in order to establish what information respond to the questions What? Where? How? When? and Why? instruments of knowledge management are needed in order to determine what knowledge is qualified to be intellectually active.knowledge, knowledge management, intelligent organization, informational technologies, knowledge exchange, collaborative networks, apportion intelligent instruments

    How do top- and bottom-performing companies differ in using business analytics?

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    Purpose Business analytics (BA) has attracted growing attention mainly due to the phenomena of big data. While studies suggest that BA positively affects organizational performance, there is a lack of academic research. The purpose of this paper, therefore, is to examine the extent to which top- and bottom-performing companies differ regarding their use and organizational facilitation of BA. Design/methodology/approach Hypotheses are developed drawing on the information processing view and contingency theory, and tested using multivariate analysis of variance to analyze data collected from 117 UK manufacture companies. Findings Top- and bottom-performing companies differ significantly in their use of BA, data-driven environment, and level of fit between BA and data-drain environment. Practical implications Extensive use of BA and data-driven decisions will lead to superior firm performance. Companies wishing to use BA to improve decision making and performance need to develop relevant analytical strategy to guide BA activities and design its structure and business processes to embed BA activities. Originality/value This study provides useful management insights into the effective use of BA for improving organizational performance

    Knowledge management, innovation and big data: Implications for sustainability, policy making and competitiveness

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    This Special Issue of Sustainability devoted to the topic of “Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness” attracted exponential attention of scholars, practitioners, and policy-makers from all over the world. Locating themselves at the expanding cross-section of the uses of sophisticated information and communication technology (ICT) and insights from social science and engineering, all papers included in this Special Issue contribute to the opening of new avenues of research in the field of innovation, knowledge management, and big data. By triggering a lively debate on diverse challenges that companies are exposed to today, this Special Issue offers an in-depth, informative, well-structured, comparative insight into the most salient developments shaping the corresponding fields of research and policymaking
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