Information Technology for Management: Solving Social and Business Problems through IT

Information Technology for Management: Solving Social and Business Problems through IT

ITBS 2023 Main Track and ISM 2023 Thematic Track, Held as Part of FedCSIS 2023, Warsaw, Poland, September 17-20, 2023, Extended and Revised Selected Papers

Watrobski, Jaroslaw; Chmielarz, Witold; Ziemba, Ewa

Springer International Publishing AG

05/2024

284

Mole

9783031616563

15 a 20 dias

Descrição não disponível.
.- IT in Improving of Management Systems.

.- Towards Re-identification of Expert Models: MLP-COMET in the Evaluation of Bitcoin Networks.

.- MBCO: The Materials-Based Business Case Ontology from BPMN-EMMO Integration.

.- Digital Technologies in Consulting - Impact of the COVID-19 Pandemic.

.- Integrating Non-Financial Data into a Creative Accounting Detection Model: A Study in the Saudi Arabian Context.

.- Effective Communication of IT Costs and IT Business Value.

.- Approaches to Improving of Social Problems.

.- A Quantitative and Qualitative Exploration of Critical Factors in the IAI-CGM Framework: The Perspective of Saudi Patients with Type 1 Diabetes Mellitus.

.- Technostress Experiences under Hybrid Work Conditions in South Africa: Causes and Coping Mechanisms.

.- Experimenting Emotion-Based Book Recommender Systems with Social Data.

.- Sign Language Interpreting - Assessment of the Efficiency of the Translation Model.

.- Methods of Solving Business.

.- Sustainable Smart Cities: A Comprehensive Framework for Sustainability Assessment of Intelligent Transport Systems.

.- Brand Dynamics and Social Media Strategies During the Russia-Ukraine War: Insights from Poland.

.- Opportunities and Obstacles of using Gamification in the Recruiting Process.

.- A Literature Review Based Insight into Agile Mindset Through a Lens of Six C's Grounded Theory Model.
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business information systems;project management;computer applications;artificial intelligence;business intelligence;linked open data;multi-criteria decision-making;RDF - resource description framework;deep learning