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[null,null,"Titolo",null,"Marketing and Smart Technologies : Proceedings of ICMarkTech 2023, Volume 1 / / edited by José Luís Reis, Jiří Zelený, Beáta Gavurová, José Paulo Marques dos Santos"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9789819715527"]
[{"$nulls":4},"9789819715510"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (859 pages)"]
[null,null,"Collana",null,"Smart Innovation, Systems and Technologies, , 2190-3026 ; ; 386"]
[null,null,"Disciplina",null,"658.80028563"]
[null,null,"Soggetti",null,"Internet of things"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Quantitative research"]
[{"$nulls":4},"Internet of Things"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Data Analysis and Big Data"]
[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 -- Contents -- About the Editors -- Part I Artificial Intelligence Applied in Marketing -- 1 Social Media Presence Impacts AI Influencer's Endorsement: An Empirical Evidence -- 1.1 Introduction -- 1.2 Literature Review and Hypotheses Development -- 1.2.1 Social Media Presence -- 1.2.2 Fantasy -- 1.3 Pilot Study -- 1.3.1 Methodology -- 1.3.2 Analysis and Results -- 1.3.3 Discussion -- 1.4 Main Study -- 1.4.1 Methodology -- 1.4.2 Analysis and Results -- 1.4.3 Discussion -- 1.5 Limitations and Future Research Directions -- References -- 2 GSP Internet Users Based on Their Navigation Preferences: Second Round-Law Sentences -- 2.1 Introduction -- 2.2 Data Mining Applied to Educational Environments -- 2.3 Description of the Problem -- 2.3.1 GSP Algorithm -- 2.3.2 GSP_M Algorithm -- 2.4 Experimentation -- 2.5 Conclusion -- References -- 3 Artificial Intelligence in the Development of Eco-innovations -- 3.1 Introduction -- 3.2 Theoretical Background -- 3.2.1 AI in Product Innovation Development -- 3.2.2 AI in the Development of Eco-innovations -- 3.3 Research Design -- "]
[{"$nulls":4},"3.3.1 Data and Scope -- 3.3.2 Bibliometric Analysis -- 3.4 Results -- 3.5 Discussion and Conclusion -- References -- 4 The Authenticity of ChatGPT's Responses in the Tourism and Hospitality Sector: An Explorative Study on Human Perception of Artificial Intelligence -- 4.1 Introduction -- 4.2 Literature Review -- 4.2.1 Usage of AI in the Hospitality Sector -- 4.2.2 Usage of ChatGPT in the Tourism and Hospitality Businesses -- 4.2.3 Usage of ChatGPT and Perspectives of Customers/Tourists -- 4.3 Research Methodology -- 4.3.1 Generated Textual Content by ChatGPT -- 4.3.2 Agents Employed in Semi-standardized Interviews and Explored Topics -- 4.4 Results -- 4.4.1 Ideal Types of Interviewed Agents -- 4.5 Discussion and Final Remarks -- References."]
[{"$nulls":4},"5 Artificial Neural Networks and Discrete Choice Models: Comparing and Contrasting -- 5.1 Introduction -- 5.2 Literature Review -- 5.2.1 Artificial Neural Networks -- 5.2.2 Discrete Choice Models -- 5.2.3 ANNs Versus DCM -- 5.3 Methodology -- 5.4 Results and Findings -- 5.5 Concluding Remarks -- References -- 6 Usage of Artificial Intelligence for Advertising Creation for Social Media Marketing: ChatGPT Combined with Pictory and DALL·E -- 6.1 Introduction -- 6.2 Literature Review -- 6.3 Methodology -- 6.4 Discussion -- 6.5 Results: Real-World Case Studies -- 6.5.1 Case Study 1: Successful Social Media Marketing Campaigns Utilizing AI-Generated Advertising -- 6.5.2 Case Study 2: Challenges Faced and Lessons Learned from Implementing AI in Ad Creation from Smartly.io and Dagmar (Finnish Companies) -- 6.6 The Near Future of the Use of AI for Advertising Creation for Social Media Marketing -- 6.7 Conclusion -- References -- 7 Retail Chatbots' Main Themes and Research over Time: A Bibliometric and Content Analysis -- 7.1 Introduction -- 7.2 Literature Review -- 7.2.1 Retail Chatbots' Advantages for Retailers and Consumers -- 7.2.2 Retail Chatbots' Disadvantages for Retailers and Consumers -- 7.2.3 Main Concerns with Chatbots -- 7.3 Research Questions and Methodology -- 7.3.1 Research Questions -- 7.3.2 Methodology -- 7.4 Results -- 7.4.1 Citation Analysis: Documents with the Greatest Significance and Influence -- 7.4.2 Evolution of Published Research About Retail Chatbots -- 7.4.3 Retail Chatbots' Researched Themes and Trends -- 7.5 Final Considerations -- References -- 8 Gastronomic Consumers' Attitudes Toward AI-Generated Food Images: Exploring Different Perceptions Based on Generational Segmentation -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Research Methodology -- 8.4 Results -- 8.5 Discussion and Final Remarks -- References."]
[{"$nulls":4},"9 Negative Impacts of Human-AI Interaction in Brands: A Data Mining Exploratory Approach -- 9.1 Introduction -- 9.2 Literature Review -- 9.2.1 Artificial Intelligence -- 9.2.2 Negativity in Consumer/Brand Relationship -- 9.3 Methodology -- 9.3.1 Objective and Research Question -- 9.3.2 Netnography Approach and Web Scrapping -- 9.4 Results and Discussion -- 9.5 Conclusions -- References -- 10 What Factors Determine the Consumer Acceptance of AI-Based Services? The Case of Lithuanian Consumers -- 10.1 Introduction -- 10.2 Theoretical Background and Hypothesis -- 10.2.1 Social-Emotional Factors and the Consumer Acceptance of AI-Based Services -- 10.2.2 Functional Factors and the Consumer Acceptance of AI-Based Services -- 10.2.3 Relational Factors and the Consumer Acceptance of AI-Based Services -- 10.2.4 Consumer Acceptance and Usage of AI-Based Services -- 10.3 Methodology -- 10.4 Results and Discussion -- 10.4.1 Results of Correlation Analysis -- 10.4.2 Results of Hypothesis Testing -- 10.5 Conclusions -- Appendix 1: Results of Linear Regression: Beta Coefficients -- References -- 11 \"Ready for Your Insurance Quote?\" the Impact of Chatbot Empathy on Emotions and User Experience -- "]
[{"$nulls":4},"11.1 Introduction -- 11.2 Literature Review -- 11.2.1 Anthropomorphism and Empathy in Chatbots -- 11.2.2 The Positive Effects of Anthropomorphization and Empathy on Emotions and User Experience -- 11.2.3 The Negative Effects of Anthropomorphization and Empathy on Emotions and the User Experience -- 11.3 Research Methodology -- 11.3.1 Research Design -- 11.3.2 Participant Recruitment -- 11.3.3 Procedure and Data Collection for Retrospective Post-test Interviews -- 11.3.4 Data Analysis -- 11.4 Results -- 11.4.1 How Do Users Experience Interacting with an Empathetic Chatbot? -- 11.4.2 Synthesis of Results -- 11.5 Research Contributions -- 11.5.1 Theoretical Implications."]
[{"$nulls":4},"11.5.2 Managerial Implications -- 11.6 Limitations and Avenues for Future Research -- References -- 12 Wine Consumers' Attitudes Toward AI-Generated Images of Wine Regions: Exploring Relationship Between Preferences and Imaginative Conceptions -- 12.1 Introduction -- 12.2 Research Methodology and Conduction -- 12.3 Results -- 12.4 Discussion and Final Remarks -- References -- Part II Customer Data Management and CRM -- 13 Measuring Leadership Through CELID-S: A Contemporary Perspective -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Methodology -- 13.3.1 Data Collection Techniques -- 13.4 Data Analysis -- 13.4.1 Analysis of Results -- 13.4.2 Reliability or Trustworthiness Analysis -- 13.4.3 Relationship Between Leadership Styles -- 13.4.4 Work Satisfaction -- 13.4.5 Relationship Between Leadership and Satisfaction -- 13.5 Conclusions -- References -- Part III Data Mining and Big Data-Marketing Data Science -- 14 Analyzing the Framework Conditions for Digital Entrepreneurship. An Empirical Evaluation of Country Performance -- 14.1 Introduction -- 14.2 Literature Review -- 14.3 Research Methodology -- 14.4 Results and Discussions -- 14.5 Conclusions -- References -- 15 Profiling Online and Physical Supermarket Customers Using Factor and Clustering Methods -- 15.1 Introduction -- 15.2 Related Work -- 15.2.1 Profiling Supermarket Customers Through Transactions and Questionnaires -- 15.2.2 Profiling Supermarket Customers Based on Purchased Products Characteristics -- 15.3 Methods -- 15.3.1 Overview of Analysis Process -- 15.3.2 Data Collection and Preparation -- 15.3.3 Factor and Cluster Analysis -- 15.4 Analysis Results -- 15.4.1 MCA Results -- 15.4.2 HCPC Results -- 15.5 Discussion -- 15.6 Conclusion -- References -- 16 Data-Driven Insights: Analysing Variables in Black Soldier Fly Larvae's Transformation of Organic Waste -- 16.1 Introduction."]
[{"$nulls":4},"16.2 Materials and Methods -- 16.2.1 Organic Waste Sampling -- 16.2.2 Organic Waste Pretreatment -- 16.2.3 Organic Waste Characterisation -- 16.2.4 Experiment Design -- 16.2.5 Bromatological Characteristics of the Larvae -- 16.2.6 Manure Characterisation -- 16.3 Results -- 16.3.1 Waste Characterisation -- 16.3.2 Biotransformation -- 16.4 Discussion -- 16.5 Conclusions -- References -- 17 Big Data in Journalism in Ecuador -- 17.1 Introduction -- 17.2 Methodology -- 17.3 Results -- 17.4 Conclusions -- References -- Part IV Digital Marketing and Branding -- 18 Destination Brands Experienced Through Digital Platforms: A Semiotic Approach for the Interpretation of a Case Study -- 18.1 Introduction -- 18.2 Theoretical Background -- 18.2.1 Marketing and Branding of Places -- 18.2.2 Tourism Marketing and Destination Brands -- 18.2.3 New Technologies in Tourism Digital Platforms -- 18.3 Research Methodology -- 18.3.1 Analysis Framework: Semiotic Structures and Interactional Regimes -- 18.3.2 Analysis Protocol -- 18.4 Application in Case -- 18.4.1 Case Presentation -- 18.4.2 Case Study -- 18.5 Conclusion -- References -- 19 Resilience and Transformation: Examining Marketing Strategies "]
[{"$nulls":4},"and Consumer Behavior in a COVID-19 World Connected by Social Media -- 19.1 Introduction -- 19.2 Consumer Behavior During the COVID-19 Period -- 19.3 Marketing in the Time of COVID-19 -- 19.4 Online Social Networks in the Time of COVID-19 -- 19.5 Final Considerations -- References -- 20 Key Pillars in Storytelling to Generate Emotional Branding -- 20.1 Introduction -- 20.1.1 Key Pillars of Emotional Branding -- 20.2 Methodology -- 20.3 Results and Discussion -- 20.3.1 Emotions that Awaken in the Storytelling of the Amaras Spot for General Emotional -- 20.3.2 Key Pillars in Storytelling of the Amarás Spot to Generate Emotional Branding -- 20.4 Conclusions -- References."]
[{"$nulls":4},"21 Emotions in Advertising and Their Connection to Consumers."]
[null,null,null,"Sommario/riassunto","This book includes selected papers presented at the International Conference on Marketing and Technologies (ICMarkTech 2023), held at Faculty of Economics and Management (FEM), Czech University of Life Sciences Prague (CZU), in partnership with University College Prague (UCP), in Prague, Czech Republic, between 30 November and 2 December 2023. It covers up-to-date cutting-edge research on artificial intelligence applied in marketing, virtual and augmented reality in marketing, business intelligence databases and marketing, data mining and big data, marketing data science, web marketing, e-commerce and v-commerce, social media and networking, geomarketing and IoT, marketing automation and inbound marketing, machine learning applied to marketing, customer data management and CRM, and neuromarketing technologies."]