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[null,"1.","Record Nr.",null,"UNISA996490366303316"]
[null,null,"Titolo",null,"The role of digital technologies in shaping the post-pandemic world : 21st IFIP WG 6. 11 Conference on e-Business, e-Services and e-Society, I3E 2022, Newcastle upon Tyne, UK, September 13-14, 2022, proceedings / / Savvas Papagiannidis [and five others] (editors)"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-15342-1"]
[null,null,"Descrizione fisica",null,"1 online resource (503 pages)"]
[null,null,"Collana",null,"Lecture notes in computer science ; ; Volume 13454"]
[null,null,"Disciplina",null,"658.84"]
[null,null,"Soggetti",null,"Electronic commerce"]
[{"$nulls":4},"Cities and towns - Technological innovations"]
[{"$nulls":4},"Information technology"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Artificial Intelligence -- Artificial Intelligence Adoption for FinTech Industries - An Exploratory Study About the Disruptions, Antecedents and Consequences -- 1 Introduction -- 2 Theory Development -- 3 Research Methodology -- 3.1 Data Collection -- 3.2 Data Analysis -- 4 Findings -- 4.1 Drivers of AI Adoption in the FinTech Industry -- 4.2 Positive Outcomes of AI Adoption in the FinTech Industry -- 4.3 Adverse Outcomes of AI Adoption in the FinTech Industry -- 5 Discussion -- 6 Conclusion -- References -- The Role of Organizational Culture on Artificial Intelligence Capabilities and Organizational Performance -- 1 Introduction -- 2 Theoretical Background and Constructs -- 2.1 Organizational Culture -- 2.2 Artificial Intelligence -- 2.3 Organizational Performance -- 3 Research Design and Hypotheses -- 4 Results -- 4.1 Measurements and Reliability -- 4.2 Hypotheses Testing -- 5 Discussion -- 6 Conclusions -- References -- Artificial Intelligence Ambidexterity, Adaptive Transformation Capability, and Their Impact on Performance Under Tumultuous Times -- 1 Introduction -- 2 Theoretical Context and Proposition -- 2.1 Artificial Intelligence and Its Ambidextrous Use -- 2.2 Adaptive Transformation Capability and Competitive Performance Under COVID-19 -- 3 Research Methodology and Dataset "]
[{"$nulls":4},"-- 3.1 Survey and Data Collection Procedure -- 3.2 Measures and Composite Operationalization -- 4 Model Specification and Analyses -- 4.1 A Composite-Based SEM -- 4.2 Proposition Testing -- 5 Discussion and Implications -- 5.1 Theoretical and Practical Implications -- References -- AI Technologies for Delivering Government Services to Citizens: Benefits and Challenges -- 1 Introduction -- 2 Literature Search Methodology -- 3 AI Technologies: An Overview -- 3.1 AI Technologies for Government."]
[{"$nulls":4},"3.2 AI Technologies for Citizens -- 4 Benefits of Using Artificial Intelligence -- 4.1 Benefits of Using Artificial Intelligence for Government -- 4.2 Benefits of Using Artificial Intelligence for Citizens -- 5 Challenges of Using Artificial Intelligence -- 5.1 Challenges Related to Government -- 5.2 Challenges Related to Citizens -- 6 Recommendations -- 7 Conclusion -- References -- From Responsible AI Governance to Competitive Performance: The Mediating Role of Knowledge Management Capabilities -- 1 Introduction -- 2 Background -- 3 Research Model -- 4 Methodology -- 4.1 Data Collection -- 5 Analysis -- 5.1 Measurement Model -- 5.2 Structural Model -- 6 Discussion -- 6.1 Implications for Research -- 6.2 Implications for Practice -- 6.3 Limitations and Future Research -- References -- The \"Other\" Agent: Interaction with AI and Its Implications on Social Presence Perceptions of Online Customer Experience -- 1 Introduction -- 2 Literature Review -- 2.1 AI-Based Agents -- 2.2 Anthropomorphism, Para-Social Interaction and Personalisation -- 2.3 Social Presence of the Customer Experience -- 3 Methodology -- 3.1 Sample -- 3.2 Measures and Procedure -- 4 Analysis and Results -- 4.1 Measurement Model -- 4.2 Hypotheses Testing -- 5 Discussion and Conclusion -- 5.1 Discussion -- 5.2 Limitations -- 5.3 Future Research -- 5.4 Conclusion -- References -- Deriving Design Principles for AI-Adaptive Learning Systems: Findings from Interviews with Experts -- 1 Introduction -- 2 Theoretical Background -- 3 Research Method -- 4 Presentation of Results -- 4.1 Meaningful Features and Functionalities of AI-ALS -- 4.2 Features and Functionalities of AI-ALS that Had Issues -- 4.3 Meaningful Features and Functionalities of AI-ALS -- 5 Discussion -- 6 Implications and Future Recommendations -- References."]
[{"$nulls":4},"The Impact of Functional and Psychological Barriers on Algorithm Aversion - An IRT Perspective -- 1 Introduction -- 2 Background -- 2.1 AI Decision and Algorithm Aversion -- 2.2 Innovation Resistance -- 3 Model and Hypothesis Development -- 3.1 Usage Barrier -- 3.2 Value Barrier -- 3.3 Risk Barrier -- 3.4 Tradition Barrier -- 3.5 Image Barrier -- 4 Methodology -- 4.1 Measurement Development -- 4.2 Data Collection and Analysis -- 5 Results and Discussion -- 5.1 Hypothesis Test Results -- 5.2 Implications -- 5.3 Limitations and Future Research -- References -- Data and Analytics -- Understanding Opportunities and Threats of Learning Analytics in Higher Education - A Students' Perspective -- 1 Motivation -- 2 Theoretical Foundation -- 2.1 Learning Analytics -- 2.2 Opportunities of Learning Analytics -- 2.3 Threats of Learning Analytics -- 3 Research Design -- 4 Results -- 4.1 Learning Analytics Opportunities from Students' Perspective -- 4.2 Learning Analytics Threats from Students' Perspective -- 5 Discussion -- 6 Conclusion -- References -- Methods and Tools for Social Media Analytics to Support Citizen Relationship Management: A Dataset Analysis of Tweets from Germany and South Africa -- 1 Introduction -- 2 Literature Review -- 3 Research Method -- 4 Results and Analysis -- 4.1 Social Media Monitoring with NVivo -- 4.2 Performing SMA Sentiment Analysis with uClassify -- 4.3 Visualisation in SMA -- 5 Discussion -- 6 Conclusion and Future Work -- References -- The "]
[{"$nulls":4},"Impact of Machine Learning-Based Techniques on the Scouting and Screening Processes of Early-Stage Venture Capital Firms -- 1 Introduction -- 2 Related Work -- 3 Research Design -- 4 Findings and Discussion -- 4.1 ML Impacts in the Sourcing Phase -- 4.2 ML Impacts in the Screening Process -- 4.3 The Overall Impact of AI in Early-Stage VC -- 5 Conclusion -- References."]
[{"$nulls":4},"Extended SESIM: A Tool to Support the Generation of Synthetic Datasets for Human Activity Recognition -- 1 Introduction -- 2 Related Works -- 2.1 Smart Environments -- 2.2 SE and HAR: A Research Timeline -- 2.3 Human Activities -- 3 Proposed Approach -- 3.1 Simulation -- 3.2 ML for HAR -- 4 Experimental Work and Results -- 4.1 Results -- 5 Conclusion and Future Work -- References -- Careers and ICT -- Virtual Internships as Employer-Led Initiatives: Success Criteria and Reflections on the Diversification of Internships -- 1 Introduction -- 2 Success Factors for Employer-Run Virtual Internships -- 2.1 Information Accuracy (Expectation Management) -- 2.2 Social Influence (Role of Important and Significant Others) -- 2.3 Support and Assistance (Resources, Mentoring and Training) -- 3 Methods -- 3.1 Data Collection Procedure -- 3.2 Participant Description -- 3.3 Measures -- 4 Results -- 4.1 Description of the Internship Experience -- 4.2 Correlations and Group Comparisons -- 4.3 Hypothesis Testing and Exploratory Analyses -- 5 Discussion and Conclusions -- 5.1 Practical Implications and Key Lessons -- 5.2 Limitations of Current Study -- 5.3 Future Research Trajectories -- References -- Teachers' Preparedness for Integrating Programming and Computational Thinking in Art and Crafts -- 1 Introduction -- 1.1 Moving from Curriculum to Practice - New Demands on the Teachers? -- 2 Background: Programming and CT in Compulsory Education -- 3 Theoretical Foundation: Barriers for Technology Integration -- 4 Research Design, Methods and Data -- 4.1 Interviews -- 4.2 Coding and Analysis of Data -- 5 Findings -- 5.1 First-Order Barriers -- 5.2 Second-Order Barriers -- 6 Summary and Implications for Further Work -- References -- Factors Influencing Women's IT Career Choice in South Africa -- 1 Introduction -- 2 Literature Review -- 2.1 Intrinsic Factors."]
[{"$nulls":4},"2.2 Extrinsic Factors -- 2.3 IT as a Career -- 2.4 Conceptual Model -- 3 Research Design -- 4 Women in IT - Results -- 4.1 Measurement Items -- 4.2 Exploratory Factor Analysis -- 4.3 Pearson's Correlations -- 4.4 Key Findings and Recommendations -- 5 Conclusions and Future Research -- References -- Digital Innovation and Transformation -- Digital Transformation in the Public Sector: Investigating Success Factors in IRIDA System -- 1 Introduction -- 2 Theoretical Background -- 3 Methodology -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- The Role of Digital Transformation in Fostering Transparency: An e-Court System Case Study -- 1 Introduction -- 2 Relevant Studies -- 3 The Case of e-Court System in the KRI -- 4 Research Methodology -- 5 Results and Discussion -- 6 Conclusion -- References -- How Can Hackathons Facilitate Employee-Driven Digital Innovation in Public Organizations? -- 1 Introduction -- 2 Background -- 3 Research Methodology -- 3.1 Problem Formulation -- 3.2 Building, Intervention, and Evaluation -- 3.3 Reflection and Learning -- 3.4 Formalization of Learning -- 4 Expected Results -- References -- Agility as a Driver of Digital Transformation - a Literature Review -- 1 Introduction -- 2 Methodology -- 3 Analysis and Results -- 3.1 Connections Between Agility and Digital Transformation -- 3.2 Agility Comprehension -- 3.3 Relevant Agile Practices, Methods, and Scaling Frameworks -- 3.4 Agility Characteristics -- 4 Discussion -- 5 Conclusion and Limitations -- Appendix -- References -- Clustering Design Science Research Based on the Nature "]
[{"$nulls":4},"of the Designed Artifact -- 1 Introduction -- 2 Design Science Research: Classifying the Design Artifacts, Knowledge Contributions, and Research Activities -- 3 Methodology -- 4 Findings -- 4.1 Design Science Studies Presenting Constructs -- 4.2 Design Science Studies Presenting Models."]
[{"$nulls":4},"4.3 Design Science Studies Presenting Methods."]