Academic literature on the topic 'Business intelligence systems'

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Journal articles on the topic "Business intelligence systems"

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G., Mahendran. "Business Intelligence." Shanlax International Journal of Commerce 7, S1 (2019): 261–62. https://doi.org/10.5281/zenodo.3451722.

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Business Intelligence systems combine operational data with analytic tools to present complex and competitive information to planners and decision-makers. Although business intelligence systems are widely used in industry, research about them is limited. Effective business intelligence systems must account for goal-oriented behavior and decision-makers.  
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Francesco Di Tria, Ezio Lefons, and Filippo Tangorra. "Evaluation of Business Intelligence Systems." International Journal of Information Processing and Management 4, no. 3 (2013): 222–37. http://dx.doi.org/10.4156/ijipm.vol4.issue3.22.

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Rouhani, Saeed, Amir Ashrafi, Ahad Zare Ravasan, and Samira Afshari. "Business Intelligence Systems Adoption Model." Journal of Organizational and End User Computing 30, no. 2 (2018): 43–70. http://dx.doi.org/10.4018/joeuc.2018040103.

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Decision support and business intelligence systems have been increasingly adopted in organizations, while understanding the nature of affecting factors on such adoption decisions need receiving much academic interest. This article attempts to provide an in-depth analysis toward understanding the critical factors which affect the decision to adopt business intelligence (BI) in the context of banking and financial industry. In this regard, it examines a conceptual model that shows the impacts of different technological, organizational, and environmental factors in the decision to adopt BI by a f
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Stecyk, Adam. "Business Intelligence systems in SMEs." European Journal of Service Management 27 (2018): 409–13. http://dx.doi.org/10.18276/ejsm.2018.27/2-50.

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Tunowski, Remigiusz. "Organization Effectiveness and Business Intelligence Systems. Literature Review." Management and Business Administration. Central Europe 23, no. 4 (2015): 55–73. http://dx.doi.org/10.7206/mba.ce.2084-3356.157.

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Grünwald, Markus, and Dirk Taubner. "Business Intelligence." Informatik-Spektrum 32, no. 5 (2009): 398–403. http://dx.doi.org/10.1007/s00287-009-0374-1.

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Herring, Jan P. "Business Intelligence." Journal of Business Strategy 14, no. 3 (1993): 10–12. http://dx.doi.org/10.1108/eb039552.

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Glancy, Fletcher H., and Surya B. Yadav. "Business Intelligence Conceptual Model." International Journal of Business Intelligence Research 2, no. 2 (2011): 48–66. http://dx.doi.org/10.4018/jbir.2011040104.

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A business intelligence conceptual model (BISCOM) is proposed as a process-focused design theory for developing, understanding, and evaluating business intelligence (BI) systems. Previous work has concentrated on subsets of the BI systems, use of BI tools, and specific business functional area requirements. BISCOM provides a unified and comprehensive design theory that integrates and synthesizes existing research. It extends existing research by proposing functionality that does not currently exist in BI systems. The BISCOM is validated through descriptive methods that demonstrate the model ut
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Hawking, Paul, and Carmine Sellitto. "Business Intelligence Strategy." International Journal of Enterprise Information Systems 11, no. 1 (2015): 1–12. http://dx.doi.org/10.4018/ijeis.2015010101.

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Although Business Intelligence is seen as priority by many companies, the level of benefits achieved varies significantly between firms. Researchers have indicated that not having an effective Business Intelligence strategy is a significant issue in regards to trying to realize organizational benefits. This paper adopting a case study method investigates an Australian energy company's Business Intelligence adoption and the development of a Business Intelligence strategy that directly informed the firm's information needs. The important elements of this strategy included using a set of guiding
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N. Montero, Javier, and Mary L. Lind. "Determining Business Intelligence Usage Success." International Journal of Computer Science and Information Technology 12, no. 6 (2020): 45–67. http://dx.doi.org/10.5121/ijcsit.2020.12604.

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Business intelligence systems are highly complex systems that senior executives use to process vast amounts of information when making decisions. Business intelligence systems are rarely used to their full potential due to a poor understanding of the factors that contribute to system success. Organizations using business intelligence systems frequently find that it is not easy to evaluate the effectiveness of these systems, and researchers have noted that there is limited scholarly and practical understanding of how quality factors affect information use within these systems. This quantitative
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Dissertations / Theses on the topic "Business intelligence systems"

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Crossland, Maria. "How business intelligence is adding business value." Master's thesis, University of Cape Town, 2010. http://hdl.handle.net/11427/10287.

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Includes bibliographical references (leaves 67-72).<br>Business Intelligence (BI) continues to top the list of CIO priorities, investment in BI technologies continues to grow and organizations are becoming increasingly reliant on BI to help reduce costs and grow revenues. However, structured measurement and monitoring of the business value that can be attributed to BI investment remain elusive. This study used a multiple case study approach to examine how BI is adding value to organizations, what processes and methods are being followed for the evaluation of the business value that BI delivers
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Kashora, Kudzai. "Leveraging mobile business intelligence to create strategic business value." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/13218.

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Includes bibliographical references.<br>Currently, there is a growing need for mobile Business Intelligence (BI) in the business world as the nature of work is changing and employees are more mobile than ever before. Mobile BI promises portability and pervasive access to BI, making it a topic high on many directors’ agendas; however the tangible and intangible benefits of mobile BI are still not well understood. Coupled with this, BI practitioners’ are sceptical about the real business value of delivering BI reports to mobile devices and how this undertaking can bring about organizational chan
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Chamoun, Christoffer. "Self-Service Business Intelligence : Kritiska framgångsfaktorer för att tillämpa Self-Service Business Intelligence." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15645.

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Self-service Business Intelligence är idag ett relativt nytt koncept och det blir vanligare idag att verksamheter börjar röra sig mot denna nya trend inom Business Intelligence för att att göra sina användare mer flexibla i sitt beslutsfattande. Anpassningen idag till Self- service BI är idag är låg och har sjunkit de senare trots stora investeringar. Konceptet med Self-service BI är kan vara svårt för användarna att förstå och det finns ett antal faktorer som kan bidra till att öka anpassningen och uppnå framgångar med att tillämpa SSBI. Denna studien syftar till att ta red
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Ahmad, Tanvir. "Design and Implementation of Business Intelligence Systems." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-156662.

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The goal of this project was to investigate the limitations of current Business Intelligence System (BI System) which was needed to re-design its architecture and embed two new modules. These two modules were named as Survey Form and Statistics Report. The survey form has a very dynamic behavior, for example the administrator can generate different types of surveys instantly by drag drop quick functionality of the interface and he can also send that surveys to the users. The user will give the answers of survey questions and send them back to the management of the company where survey form mod
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Khalaf, Patrik. "Mobile business intelligence : För en lyckad mobile business intelligence lösning." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15752.

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Allt fler organisationer börjar se nyttan med Business Intelligence och varför det bör implementeras i sin verksamhet. Genom att använda sig av beslutsstödsystem kan organisationer samla ihop och bearbeta affärs-data och på så sätt få ut mer av sin verksamhet. Idag räcker det inte längre att ha tillgång till endast företagsinformationen inom verksamheten utan det behövs också kunna utnyttja realtids datan genom de mobila enheterna, detta genom Mobile Business Intelligence. Det handlar om en mobil variant av den traditionella business Intelligence (BI).  Med tanke på den mobila användningen öka
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Lindahl, Alexander, and Joel Gustafsson. "Business Intelligence för små företag." Thesis, Uppsala universitet, Institutionen för informatik och media, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-386497.

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Globaliseringen av ekonomin har genererat globaliseringen av information som varje chef har att hantera snabbt och effektivt i beslutsprocessen. Små företag är mer sårbara för att ändra affärsvillkor än större konkurrenter. För att överleva i den instabila ekonomiska miljön där de är verksamma måste småföretag kunna monitorera sina affärer och använda alla sina resurser effektivt, särskilt informationsresurser. Under det senaste decenniet har användningen av business intelligence vuxit fram som ett måste för att inte tappa marknadsfördelar. Huvudsyftet med denna uppsats
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Robles, Sebastian. "Business intelligence in Chile, recommendations to develop local applications." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/70831.

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Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, June 2011.<br>"February 2010." Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 60).<br>The volume of information generated from enterprise applications is growing exponentially, and the cost of storage is decreasing rapidly. In addition, cloud-based applications, mobile devices and social networks are becoming relevant sources of unstructured data that provide essential information for strategic decisions making. Therefore, with time, enterprise dat
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El, Harbiti Deeb. "Web-based spreadsheets and Business Intelligence : Combining a web-based spreadsheet with Pentahos Business Intelligence." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-324998.

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Business Intelligence is becoming more and more an essential element for a company’s planning, development and consistency. A company usually aims to predict and optimize the outcome of different decisions. In order to do that, it requires a tool that can perform scenario analysis or “what if” – analysis. These analyses can be performed with spreadsheets and today with the tools within business analysis being web-based, the purpose of the project is to combine a web-based spreadsheet with an analysis from a BI server. The BI server provides sample data. Should a combination be possible then a
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McHenry, John James. "Exploring Best Practices to Utilize Business Intelligence Systems." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2742.

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Organizational leaders who can manage business intelligence system (BIS) resources may achieve sustainable success in economic, political, and corporate environments. The review of professional literature indicated that effective resource management in a BIS environment requires the establishment of best practice. The purpose of this qualitative, single-case study was to explore best practices among 9 BIS practitioners for effective resource management. Participation criteria included the active engagement in BIS professional disciplines and the willingness to share their perspectives. The con
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Johansson, Christoffer. "Self service business intelligence : Grundkompetenser för slutanvändare." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15630.

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Organisationer vill hela tiden bli effektivare i allt de gör även när det kommer till business intelligence. För att effektivisera beslutstödsprocessen har organisationer börjat gå över till selfe service business intelligence där personer på en operativ nivå skapar sina egna rapporter och gör sina egna analyser. När detta sker uppkommer nya moment för personalen i organisationen och de behöver skaffa sig nya kompetenser. Vilka kunskaper behöver egentligen personalen skaffa sig? Det är det som undersöks i det här arbetet. Undersökningen kommer genomföras med hjälp av en fallstudie. Litteratur
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Books on the topic "Business intelligence systems"

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Turban, Efraim. Decision support and business intelligence systems. 9th ed. Pearson/Prentice Hall, 2011.

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1949-, King David, ed. Expert systems: Artificial intelligence in business. J. Wiley, 1985.

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Sauter, Vicki L. Decision Support Systems for Business Intelligence. John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9780470634431.

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Kautish, Sandeep, Prasenjit Chatterjee, Dragan Pamucar, N. Pradeep, and Deepmala Singh, eds. Computational Intelligence for Modern Business Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-5354-7.

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Howson, Cindi. Successful Business Intelligence. McGraw-Hill, 2008.

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T, Leondes Cornelius, ed. Intelligent knowledge-based systems: Business and technology in the new millennium. Kluwer Academic, 2005.

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Shan, Caifeng. Video Analytics for Business Intelligence. Springer Berlin Heidelberg, 2012.

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Azevedo, Ana, and Manuel Filipe Santos. Integration of data mining in business intelligence systems. Business Science Reference, 2015.

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Browne, Dean. IBM Cognos Business Intelligence V10.1 handbook. IBM, International Technical Support Organization, 2010.

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Volitich, Dan. IBM Cognos 8 Business Intelligence. McGraw-Hill, 2008.

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Book chapters on the topic "Business intelligence systems"

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Rizzi, Stefano. "Business Intelligence." In Encyclopedia of Database Systems. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_881-2.

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Rizzi, Stefano. "Business Intelligence." In Encyclopedia of Database Systems. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_881.

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Rizzi, Stefano. "Business Intelligence." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_881.

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Caserio, Carlo, and Sara Trucco. "Business Intelligence Systems." In Contributions to Management Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77679-8_3.

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Kale, Vivek. "Business Intelligence Systems." In Enterprise Performance Intelligence and Decision Patterns. Auerbach Publications, 2017. http://dx.doi.org/10.4324/9781351228428-10.

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Negash, Solomon, and Paul Gray. "Business Intelligence." In Handbook on Decision Support Systems 2. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-48716-6_9.

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Gronwald, Klaus-Dieter. "BI: Business Intelligence." In Integrated Business Information Systems. Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-53291-1_13.

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Gronwald, Klaus-Dieter. "BI: Business Intelligence." In Integrated Business Information Systems. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-59811-5_5.

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Kazeli, Hariklea. "Cloud Business Intelligence." In Business Information Systems Workshops. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11460-6_26.

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Casati, Fabio, Umeshwar Dayal, and Ming-Chien Shan. "Business Operation Intelligence." In Databases in Networked Information Systems. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36233-9_17.

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Conference papers on the topic "Business intelligence systems"

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Jaganathan, Humashankar Vellathur, Prakash Murugesan, Sairam Madasu, and Imran Ur Rehman. "Artificial Intelligence Embedded Customer Relationship Management for Business-to-Business Firms using Improved Long Short-Term Memory." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721741.

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Bouziane, El Mahi, Hamza Abdelmalek, Lamya Benaddi, et al. "UML Functional Aspects in Business-to-Business: Some Lessons Learned." In 2024 3rd International Conference on Embedded Systems and Artificial Intelligence (ESAI). IEEE, 2024. https://doi.org/10.1109/esai62891.2024.10913753.

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Liu, Jinxia, and Pei Liu. "Research on the Application of Artificial Intelligence Technology in Traditional Business Intelligence Systems." In 2024 4th International Symposium on Computer Technology and Information Science (ISCTIS). IEEE, 2024. http://dx.doi.org/10.1109/isctis63324.2024.10698971.

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Indumathi, P., M. Suresh Kumar, M. Umamaheswari, A. Anisha Alex, B. Adalarasu, and S. Thangamani. "Sustainable Business Approaches for FMCG Companies Leveraging Artificial Intelligence." In 2025 7th International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2025. https://doi.org/10.1109/iciss63372.2025.11076260.

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Khaldy, Mohammad Al, and Ameen Shaheen. "NLP Systems for Intelligent Report Generation in Business." In 2025 1st International Conference on Computational Intelligence Approaches and Applications (ICCIAA). IEEE, 2025. https://doi.org/10.1109/icciaa65327.2025.11013185.

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Usha, Pagadala, and Sunil Kumar Puli. "Machine Learning for Strategic Business Intelligence: A Short Review." In 2024 IEEE International Conference on Computing, Applications and Systems (COMPAS). IEEE, 2024. https://doi.org/10.1109/compas60761.2024.10796605.

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Mositsa, Ramakolote Judas, John Andrew van der Poll, and Cyrille Dongmo. "Annotating a Business Intelligence Framework Through Formal Specification Observations." In 2024 15th International Conference on Information and Communication Systems (ICICS). IEEE, 2024. http://dx.doi.org/10.1109/icics63486.2024.10638297.

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Dasgupta, Supratim, and Vamsi Krishna Vankayala. "Developing Real Time Business Intelligence Systems the Agile Way." In 2007 1st Annual IEEE Systems Conference. IEEE, 2007. http://dx.doi.org/10.1109/systems.2007.374652.

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Krneta, Dragoljub, Dragica Radosav, and Biljana Radulovic. "Realization business intelligence in commerce using Microsoft Business Intelligence." In 2008 6th International Symposium on Intelligent Systems and Informatics (SISY 2008). IEEE, 2008. http://dx.doi.org/10.1109/sisy.2008.4664943.

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Mach, Maria Antonina, and M. Salem Abdel-Badeeh. "Intelligent techniques for business intelligence in healthcare." In 2010 10th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2010. http://dx.doi.org/10.1109/isda.2010.5687209.

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Reports on the topic "Business intelligence systems"

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Vuyyuru, Tejaswini. Using Predictive Maintenance techniques and Business Intelligence to develop smarter factory systems for the digital age. Iowa State University, 2018. http://dx.doi.org/10.31274/cc-20240624-1566.

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Pasupuleti, Murali Krishna. Empathetic AI in Action: Transforming Customer Service with Emotional Intelligence. National Education Services, 2025. https://doi.org/10.62311/nesx/rr725.

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Abstract: This article explores the transformative impact of Emotionally Intelligent AI on customer service, focusing on how AI systems are designed to understand and respond to human emotions with empathy and precision. It delves into the core technologies, such as sentiment analysis, emotion recognition models, and reinforcement learning, that enable AI to provide emotionally aware interactions. Practical applications are discussed, including AI-powered customer support, personalized experiences, and crisis management solutions. The Article also covers the psychological foundations of AI-dri
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Canto, Patricia, ed. The role of vocational training knowledge intensive business services. (Main conclusions). Universidad de Deusto, 2020. http://dx.doi.org/10.18543/vyqr9353.

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In the global economic model, the service sector continues to gain ground on the manufacturing sector and trends such as the integration of new technologies into production processes are advancing inexorably. Advanced economies are pushed to specialise, supported by their regional innovation systems, and cities are emerging as key and strategic centres of activity. In this context, Knowledge Intensive Business Services (KIBS) are presented as critical due to their capacity to promote innovation within the regional productive fabric and smart specialisation strategies, the promotion of advanced
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Danylchuk, Hanna B., and Serhiy O. Semerikov. Advances in machine learning for the innovation economy: in the shadow of war. Криворізький державний педагогічний університет, 2023. http://dx.doi.org/10.31812/123456789/7732.

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This preface introduces the selected and revised papers presented at the 10th International Conference on Monitoring, Modeling &amp; Management of Emergent Economy (M3E2 2022), held online in Ukraine, on November 17-18, 2022. The conference aimed to bring together researchers, practitioners, and students from various fields to exchange ideas, share experiences, and discuss challenges and opportunities in applying computational intelligence and data science for the innovation economy. The innovation economy is a term that describes the emerging paradigm of economic development that is driven by
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Rihm, Alfredo, Carolina Piamonte, Eduardo Antonio Restrepo Lagos, Magda Correal, and Paula Gabriela Guerra Morán. Digital Transformation of Solid Waste Management: Waste Collection Innovation, Business Intelligence, and Digital Technologies to Transition Waste Management Towards Circularity in Latin America and the Caribbean. Edited by Claudia M. Pasquetti. Inter-American Development Bank, 2024. http://dx.doi.org/10.18235/0013169.

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If you are interested in technology and innovation, and have been wondering what are the new trends in technological and digital innovation in the solid waste sector in Latin America and the Caribbean, this publication is for you! The transition to the circular economy, climate action, the fourth industrial revolution bring new challenges to operators in the sector. Key challenges highlighted include the need for robust data and the digitization of waste management systems to meet the objectives of the circular economy. The text details the efforts of organizations such as the IDB to develop d
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Nowinska, Agnieszka Urszula, and Gisele Msann. AI disruption in chartering in Danish Shipping. Aalborg University Open Publishing, 2025. https://doi.org/10.54337/aau.bk2_2025.

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Our research highlights the current state and trends of artificial intelligence (AI) adoption in Denmark’s chartering, particularly in the dry bulk and tanker segments. Companies in the dry bulk sector are leading AI adoption, with the tanker segment closely following and adoption rates in our sample appear higher than national averages reported by consultancies. Most firms are in either the experimental phase or transitioning toward more integrated AI systems, often opting for hybrid models that allow them to maintain internal control over key processes. Factors such as company size and matur
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Li, Richard. DeepSeek: Revolutionising the AI industry. LegalOne Global Limited, 2025. https://doi.org/10.62436/a-1740063218021.

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Recently, DeepSeek, a Chinese artificial intelligence (AI) startup, has made headlines with its groundbreaking advancements in AI technology. Founded in 2023 by entrepreneur Liang Wenfeng, DeepSeek has quickly risen to prominence, challenging established AI giants like OpenAI and Google. DeepSeek, headquartered in Hangzhou, China, is known for its cost-efficient AI models and open-source approach, making advanced AI technology accessible to a wider range of businesses and developers. Open-source AI refers to systems whose source code, datasets, and model parameters are freely available for any
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Marsden, Eric, and Véronique Steyer. Artificial intelligence and safety management: an overview of key challenges. Foundation for an Industrial Safety Culture, 2025. https://doi.org/10.57071/iae290.

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Artificial intelligence based on deep learning, along with big data analysis, has in recent years been the subject of rapid scientific and technological advances. These technologies are increasingly being integrated into various work environments with the aim of enhancing performance and productivity. This dimension of the digital transformation of businesses and regulatory authorities presents both significant opportunities and potential risks for industrial safety management practices. While there are numerous expected benefits, such as the ability to process large volumes of reliability dat
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Khan, Samir. AI in Wonderland: Engineering in the Age of Overpromised Technology. SAE International, 2025. https://doi.org/10.4271/epr2025002.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;This report explores the move from traditional industry practices to emerging technologies, specifically the integration of artificial intelligence (AI) solutions in engineering service sectors. It highlights the increasing problem of “technology washing,” when organizations overstate (sometimes deceivingly) their technology abilities and ethics, posing challenges to accountability, transparency, and trust in various fields. The rise of AI-based solutions in sectors like autonomous mobility, manufacturing, and aerospace
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Fang, Mei Lan, Judith Sixsmith, Jacqui Morris, et al. AgeTech, Ethics and Equity: Towards a Cultural Shift in AgeTech Ethical Responsibility. University of Dundee, 2023. http://dx.doi.org/10.20933/100001292.

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Population ageing is a global phenomenon which presents major challenges for the provision of care at home and in the community (ONS, 2018). Challenges include the human and economic costs associated with increasing numbers of older people with poor physical and mental health, loneliness, and isolation challenges (Mihalopoulos et al., 2020). The global ageing population has led to a growth in the development of technology designed to improve the health, well-being, independence, and quality of life of older people across various settings (Fang, 2022). This emerging field, known as “AgeTech,” r
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