{"product_id":"artificial-intelligence-technologies-in-management-and-engineering-iste-invoiced-1st-edition","title":"Artificial Intelligence Technologies in Management and Engineering (ISTE Invoiced) 1st Edition","description":"\u003cdiv data-cel-widget=\"bookDescription_feature_div\" data-csa-c-id=\"u7qumn-38oend-85jy7q-z9853p\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-asin=\"\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-content-id=\"bookDescription\" data-csa-c-type=\"widget\" data-feature-name=\"bookDescription\" class=\"celwidget\" id=\"bookDescription_feature_div\"\u003e\n\u003cdiv class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\" data-a-expander-collapsed-height=\"280\" data-a-expander-name=\"book_description_expander\"\u003e\n\u003cdiv class=\"a-expander-content a-expander-partial-collapse-content\" data-expanded=\"false\"\u003e\n\u003cdiv id=\"bookDescription_feature_div\" class=\"celwidget\" data-feature-name=\"bookDescription\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"bookDescription\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-asin=\"1604272058\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"xzst4v-oqvam5-7vyc43-dx6vtu\" data-cel-widget=\"bookDescription_feature_div\"\u003e\n\u003cdiv data-a-expander-name=\"book_description_expander\" data-a-expander-collapsed-height=\"280\" class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\"\u003e\n\u003cdiv data-expanded=\"false\" class=\"a-expander-content a-expander-partial-collapse-content\"\u003e\n\u003cdiv id=\"bookDescription_feature_div\" class=\"celwidget\" data-feature-name=\"bookDescription\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"bookDescription\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-asin=\"3662638622\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"xcc6np-eu9lp-n3nxkq-kq20rp\" data-cel-widget=\"bookDescription_feature_div\"\u003e\n\u003cdiv data-a-expander-name=\"book_description_expander\" data-a-expander-collapsed-height=\"280\" class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\"\u003e\n\u003cp\u003e\u003cspan\u003eArtificial intelligence (AI) technologies play a transformative role in several areas of knowledge, including management and engineering. Their adoption has been driven by the advancement of machine learning algorithms, increased computing power, and the availability of large volumes of data, making AI technologies indispensable for process optimization and strategic decision-making. However, organizations must invest in research, development and professional training to ensure AI is used ethically and sustainably to drive progress.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThis book makes several contributions, by not only advancing scientific and technical knowledge, but also improving efficiency and decision-making, and developing new tools and technologies.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThe main aim of \u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eArtificial Intelligence Technologies in Management and Engineering\u003c\/span\u003e\u003cspan\u003e is to provide a channel for sharing and disseminating knowledge of new advances in AI technologies in management and engineering among academics\/researchers, managers and engineers. It seeks to advance research in the field, provide practical insights for managers and engineers, and also serve as a basis for future technological innovations.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv id=\"tellAmazon_feature_div\" class=\"celwidget\" data-feature-name=\"tellAmazon\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"tellAmazon\" data-csa-c-slot-id=\"tellAmazon_feature_div\" data-csa-c-asin=\"1604272058\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"kr8uq1-6hdsp3-360bmk-1yjhm\" data-cel-widget=\"tellAmazon_feature_div\"\u003e\n\u003cdiv class=\"celwidget c-f\" data-csa-op-log-render=\"\" data-csa-c-content-id=\"DsUnknown\" data-csa-c-slot-id=\"DsUnknown-2\" data-csa-c-type=\"widget\" data-csa-c-painter=\"tell-amazon-desktop-cards\" data-csa-c-id=\"x4e48r-23r9q6-40oqn3-z8o5dh\" data-cel-widget=\"tell-amazon-desktop_DetailPage_1\"\u003e\n\u003cdiv id=\"CardInstance4nrcKDtUHw4nGXWz3Qsw-A\" data-card-metrics-id=\"tell-amazon-desktop_DetailPage_1\" data-acp-tracking=\"{}\" data-mix-claimed=\"true\"\u003e\n\u003cdiv data-asin=\"1604272058\" data-customer-id=\"\" data-marketplace=\"A1RKKUPIHCS9HS\" data-session-id=\"523-7312587-0785701\" data-logged-in=\"false\" class=\"_tell-amazon-desktop_style_tell_amazon_div__1YDZk\"\u003e\n\u003cdiv id=\"aboutauthors-section\" class=\"aboutauthors-section\"\u003e\n\u003cdiv class=\"page-section\"\u003e\n\u003cdiv data-toggle=\"collapse\" class=\"section-title collapsed\"\u003e\u003cstrong\u003eAbout the Author\u003c\/strong\u003e\u003c\/div\u003e\n\u003cdiv class=\"section-content collapsed\"\u003e\n\u003cp\u003e\u003cb\u003eCarolina Machado\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eis an associate professor with habilitation at the University of Minho, Portugal. She has lectured on HRM subjects since 1989. She is currently the Head of the HRM Work Group at the University of Minho and is also the Editor-in-Chief of the\u003cspan\u003e \u003c\/span\u003e\u003ci\u003eInternational Journal of Applied Management Sciences and Engineering\u003c\/i\u003e.\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eJ. Paulo Davim\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eis a professor at the University of Aveiro, Portugal and is also distinguished as an honorary professor in several universities\/colleges\/institutes in China, India and Spain. He has more than 35 years of teaching and research experience in mechanical and industrial engineering.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv id=\"tableofcontents-section\" class=\"tableofcontents-section\"\u003e\n\u003cdiv class=\"page-section\"\u003e\n\u003cdiv data-toggle=\"collapse\" class=\"section-title collapsed\"\u003eTable of Contents\u003c\/div\u003e\n\u003cdiv class=\"section-content collapsed\"\u003e\n\u003cp\u003ePreface xiii\u003cbr\u003e\u003ci\u003eCarolina MACHADO and J. Paulo DAVIM\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 1. From Algorithms to Applications: AI in Management and Engineering 1\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eHamed TAHERDOOST and Mitra MADANCHIAN\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e1.1. Introduction 1\u003cbr\u003e1.2. Foundations of artificial intelligence 2\u003cbr\u003e1.3. AI in management 5\u003cbr\u003e1.4. AI in engineering 7\u003cbr\u003e1.5. Comparative taxonomy of AI applications 9\u003cbr\u003e1.6. Challenges and limitations 10\u003cbr\u003e1.7. Future directions 12\u003cbr\u003e1.8. Conclusion 12\u003cbr\u003e1.9. References 13\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 2. Generational Perspectives on AI (From Baby Boomers to Gen Z): Understanding, Perceived Usefulness, Motivation to Adopt and Risk Perception 19\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eFlor MORTON, Teresa TREVIÑO-BENAVIDES, Daniel Javier de la Garza MONTEMAYOR and Ana Valdés LOYOLA\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e2.1. Introduction 19\u003cbr\u003e2.2. Literature review 20\u003cbr\u003e2.3. Methodology 24\u003cbr\u003e2.4. Findings 25\u003cbr\u003e2.5. Discussion and conclusion 39\u003cbr\u003e2.6. References 43\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 3. Smart Decisions: How AI Is Transforming Everyday Management and Engineering Practices 47\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSoha RAWAS, Cerine TAFRAN, Agariadne Dwinggo SAMALA, Feri FERDIAN and Yudha Aditya FIANDRA\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e3.1. Introduction 47\u003cbr\u003e3.2. What is AI? A practical overview 49\u003cbr\u003e3.3. AI for smarter management practices 50\u003cbr\u003e3.4. AI in engineering: enhancing efficiency without coding 53\u003cbr\u003e3.5. Easy-to-use AI tools for non-technical professionals 56\u003cbr\u003e3.6. Ethical and organizational considerations 58\u003cbr\u003e3.7. Future outlook: embracing AI with confidence 59\u003cbr\u003e3.8. Conclusion 60\u003cbr\u003e3.9. Declaration 61\u003cbr\u003e3.10. References 61\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 4. Integrating AI into Business Education: Bridging the Gap Between Disciplinary Knowledge and Business Performance 65\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eLaura Esther Zapata CANTÚ and Martha Elena Moreno BARBOSA\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e4.1. Introduction 65\u003cbr\u003e4.2. AI in business practices and education 67\u003cbr\u003e4.3. Method 73\u003cbr\u003e4.4. Results 75\u003cbr\u003e4.5. Discussion and conceptual model 78\u003cbr\u003e4.6. Conclusions 82\u003cbr\u003e4.7. Declaration 84\u003cbr\u003e4.8. References 84\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 5. Holistic Management Quo Vadis? Designing Management Dispositive and Metamorphic Possibilities in the age of AI 89\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePatrick BARETTO and Qeis KAMRAN\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e5.1. Introduction 89\u003cbr\u003e5.2. Designing a dispositive of knowledge 91\u003cbr\u003e5.3. Research methodology 97\u003cbr\u003e5.4. Analysis 105\u003cbr\u003e5.5. Toward an epistemic dispositive framework 120\u003cbr\u003e5.6. The architecture of the epistemic dispositive 122\u003cbr\u003e5.7. Metamorphic possibilities of the management dispositive 124\u003cbr\u003e5.8. An apology for the management dispositive: a call for strategic foresight 125\u003cbr\u003e5.9. Declaration 130\u003cbr\u003e5.10. References 131\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 6. Mapping the Use of Generative AI in Spain's Advertising Sector: Current Trends and Future Challenges 135\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eJuan Manuel Corbacho VALENCIA, Jesús Pérez SEOANE and Xabier MARTÍNEZ-ROLÁN\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e6.1. Introduction 136\u003cbr\u003e6.2. Global perspectives on AI in advertising and creative processes 137\u003cbr\u003e6.3. Methodology 146\u003cbr\u003e6.4. Analysis of the results 148\u003cbr\u003e6.5. Conclusions 153\u003cbr\u003e6.6. References 154\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 7. Emotional Nudging in the Rise of Affective Artificial Intelligence 159\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eCristiana Cerqueira LEAL and Benilde OLIVEIRA\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e7.1. Introduction: from nudging to AI-based emotional hypernudging 159\u003cbr\u003e7.2. Emotions and decision-making 162\u003cbr\u003e7.3. Mechanisms of emotional nudging through AI 166\u003cbr\u003e7.4. Applications of emotional nudging 171\u003cbr\u003e7.5. Ethical and societal implications 176\u003cbr\u003e7.6. Final remark: long-term impact on human behavior, trust and rationality 180\u003cbr\u003e7.7. Abbreviations 181\u003cbr\u003e7.8. Acknowledgments 181\u003cbr\u003e7.9. Declaration 181\u003cbr\u003e7.10. References 181\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 8. Agentic AI in Marketing: Opportunities, Challenges and Impact on Firm Performance 185\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eFlorin Sabin FOLTEAN and Octavian Dumitru HERA\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e8.1. Introduction 185\u003cbr\u003e8.2. AAI systems 186\u003cbr\u003e8.3. AAI systems opportunities in marketing 193\u003cbr\u003e8.4. Challenges of AAI systems adoption in marketing organizations 196\u003cbr\u003e8.5. Business value of AAI systems in marketing 198\u003cbr\u003e8.6. Conclusion 199\u003cbr\u003e8.7. References 200\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 9. AI's Role in Marketing: Mapping the Evolution of Creativity 205\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eTeresa TREVIÑO-BENAVIDES and Flor MORTON\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e9.1. Introduction 205\u003cbr\u003e9.2. Literature review 207\u003cbr\u003e9.3. Challenges and limitations of AI in marketing 216\u003cbr\u003e9.4. Future directions of AI in marketing and creativity 217\u003cbr\u003e9.5. Implications and future research 217\u003cbr\u003e9.6. References 218\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 10. Unveiling Management Research's Thematic Evolution: An Unsupervised Machine Learning – Latent Dirichlet Allocation Perspective 223\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eQeis KAMRAN\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e10.1. Introduction 224\u003cbr\u003e10.2. Method 225\u003cbr\u003e10.3. Analyses 241\u003cbr\u003e10.4. Results of the content analysis 244\u003cbr\u003e10.5. Contributing authors 249\u003cbr\u003e10.6. Most influential papers 249\u003cbr\u003e10.7. Box plotting 250\u003cbr\u003e10.8. Conclusion 251\u003cbr\u003e10.9. References 252\u003cbr\u003e10.10. Appendix 1. Application of the machine learning methodology to investigate the domain of entrepreneurship and marketing 256\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eChapter 11. The Use of AI in Human Resource Management: Barriers, Opportunities and Trends. 269\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePedro Miguel Torres BARROS and Carolina MACHADO\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e11.1. Introduction 270\u003cbr\u003e11.2. Theoretical framework 271\u003cbr\u003e11.3. Methodology 278\u003cbr\u003e11.4. Analysis and discussion of results 282\u003cbr\u003e11.5. Best practice guide for using AI in HRM 286\u003cbr\u003e11.6. Conclusion 287\u003cbr\u003e11.7. Declaration 289\u003cbr\u003e11.8. References 289\u003c\/p\u003e\n\u003cp\u003eList of Authors 293\u003cbr\u003eIndex 297\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\n\u003c\/div\u003e\n\u003cdiv data-asin=\"1604272058\" data-customer-id=\"\" data-marketplace=\"A1RKKUPIHCS9HS\" data-session-id=\"523-7312587-0785701\" data-logged-in=\"false\" class=\"_tell-amazon-desktop_style_tell_amazon_div__1YDZk\"\u003e\n\u003cspan\u003e\u003c\/span\u003e\u003cbr\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"celwidget aplus-module module-12 aplus-standard\" data-cel-widget=\"aplus-module-12\" data-csa-c-id=\"e48qwb-36wm3s-vb6e8j-pnxs9b\"\u003e\n\u003cdiv class=\"aplus-module-wrapper apm-spacing apm-floatnone apm-fixed-width\"\u003e\n\u003cdiv class=\"apm-sidemodule aplus-module-content\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cb\u003eBOOKREAD™ 5-STEP SATISFACTION GUARANTEE\u003c\/b\u003e\u003c\/strong\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003e1. No Risk, 30-Day Money-Back Guarantee. \u003cbr\u003e2. instant download. No surprises or hidden fees.\u003cbr\u003e3. Safe Payments via Credit\/Debit Card or PayPal® \u003cbr\u003e4. McAfee™ and SSL secured shopping cart.\u003cbr\u003e5. lifetime customer support.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-base\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e","brand":"My Store","offers":[{"title":"PDF","offer_id":57070147764555,"sku":null,"price":29.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1031\/1204\/8971\/files\/61ovuuYGvtL._SL1360.jpg?v=1776640580","url":"https:\/\/bookread.io\/products\/artificial-intelligence-technologies-in-management-and-engineering-iste-invoiced-1st-edition","provider":"bookread","version":"1.0","type":"link"}