Industry 4.0 technologies for business excellence: frameworks, practices, and applications
Gespeichert in:
| Weitere Verfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press
2022
|
| Ausgabe: | First edition |
| Schriftenreihe: | Demystifying technologies for computational excellence
|
| Online-Zugang: | FHD01 |
| Beschreibung: | 1 Online-Ressource (xix, 268 Seiten) |
| ISBN: | 9781000519228 |
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| 245 | 1 | 0 | |a Industry 4.0 technologies for business excellence |b frameworks, practices, and applications |c edited by Shivani Bali, Sugandha Aggarwal, Sunil Sharma |
| 250 | |a First edition | ||
| 264 | 1 | |a Boca Raton ; London ; New York |b CRC Press |c 2022 | |
| 300 | |a 1 Online-Ressource (xix, 268 Seiten) | ||
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| 490 | 0 | |a Demystifying technologies for computational excellence | |
| 505 | 8 | |a Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editors -- Contributors -- Chapter 1 Understanding the Industry 4.0 Revolution Using Twitter Analytics -- 1.1 Introduction -- 1.2 Literature Review -- 1.3 Methodology -- 1.3.1 Data Collection -- 1.3.2 Data Analysis -- 1.3.2.1 Descriptive Analysis -- 1.3.2.2 Content Analysis -- 1.3.2.3 Network Analysis -- 1.3.2.4 Topic Modeling -- 1.4 Analysis and Results -- 1.4.1 Descriptive Analysis of Tweets -- 1.4.2 CA of Tweets -- 1.4.2.1 Sentiment Analysis of Tweets -- 1.4.2.2 Emotional Scores of Tweets | |
| 505 | 8 | |a 1.4.3 Network Analytics of Tweets -- 1.4.4 Topic Modeling of Tweets -- 1.5 Discussions -- 1.5.1 The Fourth Industrial Revolution Is Characterized by What Tweets? Can We See Any Particular Patterns of Communication and Information Diffusion in These Tweets? -- 1.5.2 Which Topics and Contents Are Shared in Twitter? Can We Find Any Prevalent Topics or Contents? -- 1.5.3 What Are the Features of Those Users Who Discuss These Topics Related to Industry 4.0 on Twitter? -- 1.5.4 What Sentiments Do These Tweets Contain? What Types of Tweets Tend to Contain Sentiment? -- 1.6 Conclusions | |
| 505 | 8 | |a 1.6.1 Professional Use of Twitter -- 1.6.2 Organizational Use of Twitter -- 1.6.3 Stakeholder Engagement -- 1.6.4 Hiring -- 1.6.5 Sales Channel -- 1.6.6 Social Listening -- 1.6.7 Risk Management -- 1.7 Limitation and Future Research -- References -- Chapter 2 The Role of Universal Product Coding (UPC), Global Data Synchronization Network (GDSN) and Product Category Management in Efficient Consumer Response (ECR) -- 2.1 Background of ECR -- 2.1.1 ECR as a Profit Center in Supply Chain -- 2.1.2 ECR as a Cost Alleviator in Supply Chain -- 2.1.3 ECR and Operational Efficiency in Supply Chain | |
| 505 | 8 | |a 2.1.4 ECR as Risk Mitigator in Supply Chain -- 2.1.5 ECR and the Inventory Management in the Supply Chain -- 2.1.6 ECR as a Supply Chain Strategy -- 2.2 Framework of a Global ECR Scorecard -- 2.3 Prerequisite Initiatives for Participation in ECR -- 2.4 Mechanics of ECR -- 2.5 Special Application of ECR in Product Category Management -- 2.6 Universal Product Code (UPC) -- 2.6.1 Features of UPC Barcode -- 2.7 Overview of GDSN -- 2.7.1 Product Information Sharing through GDSN and Impact on ECR -- 2.8 ECR in India -- 2.8.1 An Example of ECR Initiative in India -- 2.8.2 Workgroups in ECR India | |
| 505 | 8 | |a 2.8.3 The Future of ECR in India -- 2.9 ECR in World -- 2.10 Conclusion -- References -- Chapter 3 Delivering Superior Customer Experience through New-Age Technologies -- 3.1 Introduction -- 3.2 Customer Experience (CX) -- 3.3 Augmented Reality (AR) -- 3.3.1 Impact of AR on CX -- 3.3.2 Industry Examples of Augmented Reality Enhancing CX -- 3.4 Artificial Intelligence (AI) -- 3.4.1 AI in the Domain of CX -- 3.4.2 Industry Examples -- 3.4.3 Issues with AI -- 3.5 Chatbots -- 3.5.1 How Chatbots Deliver a Superior CX -- 3.5.2 Issues with Chatbots -- 3.6 Conclusion -- References | |
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| 700 | 1 | |a Aggarwal, Sugandha |4 edt | |
| 700 | 1 | |a Sharma, Sunil |4 edt | |
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| contents | Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editors -- Contributors -- Chapter 1 Understanding the Industry 4.0 Revolution Using Twitter Analytics -- 1.1 Introduction -- 1.2 Literature Review -- 1.3 Methodology -- 1.3.1 Data Collection -- 1.3.2 Data Analysis -- 1.3.2.1 Descriptive Analysis -- 1.3.2.2 Content Analysis -- 1.3.2.3 Network Analysis -- 1.3.2.4 Topic Modeling -- 1.4 Analysis and Results -- 1.4.1 Descriptive Analysis of Tweets -- 1.4.2 CA of Tweets -- 1.4.2.1 Sentiment Analysis of Tweets -- 1.4.2.2 Emotional Scores of Tweets 1.4.3 Network Analytics of Tweets -- 1.4.4 Topic Modeling of Tweets -- 1.5 Discussions -- 1.5.1 The Fourth Industrial Revolution Is Characterized by What Tweets? Can We See Any Particular Patterns of Communication and Information Diffusion in These Tweets? -- 1.5.2 Which Topics and Contents Are Shared in Twitter? Can We Find Any Prevalent Topics or Contents? -- 1.5.3 What Are the Features of Those Users Who Discuss These Topics Related to Industry 4.0 on Twitter? -- 1.5.4 What Sentiments Do These Tweets Contain? What Types of Tweets Tend to Contain Sentiment? -- 1.6 Conclusions 1.6.1 Professional Use of Twitter -- 1.6.2 Organizational Use of Twitter -- 1.6.3 Stakeholder Engagement -- 1.6.4 Hiring -- 1.6.5 Sales Channel -- 1.6.6 Social Listening -- 1.6.7 Risk Management -- 1.7 Limitation and Future Research -- References -- Chapter 2 The Role of Universal Product Coding (UPC), Global Data Synchronization Network (GDSN) and Product Category Management in Efficient Consumer Response (ECR) -- 2.1 Background of ECR -- 2.1.1 ECR as a Profit Center in Supply Chain -- 2.1.2 ECR as a Cost Alleviator in Supply Chain -- 2.1.3 ECR and Operational Efficiency in Supply Chain 2.1.4 ECR as Risk Mitigator in Supply Chain -- 2.1.5 ECR and the Inventory Management in the Supply Chain -- 2.1.6 ECR as a Supply Chain Strategy -- 2.2 Framework of a Global ECR Scorecard -- 2.3 Prerequisite Initiatives for Participation in ECR -- 2.4 Mechanics of ECR -- 2.5 Special Application of ECR in Product Category Management -- 2.6 Universal Product Code (UPC) -- 2.6.1 Features of UPC Barcode -- 2.7 Overview of GDSN -- 2.7.1 Product Information Sharing through GDSN and Impact on ECR -- 2.8 ECR in India -- 2.8.1 An Example of ECR Initiative in India -- 2.8.2 Workgroups in ECR India 2.8.3 The Future of ECR in India -- 2.9 ECR in World -- 2.10 Conclusion -- References -- Chapter 3 Delivering Superior Customer Experience through New-Age Technologies -- 3.1 Introduction -- 3.2 Customer Experience (CX) -- 3.3 Augmented Reality (AR) -- 3.3.1 Impact of AR on CX -- 3.3.2 Industry Examples of Augmented Reality Enhancing CX -- 3.4 Artificial Intelligence (AI) -- 3.4.1 AI in the Domain of CX -- 3.4.2 Industry Examples -- 3.4.3 Issues with AI -- 3.5 Chatbots -- 3.5.1 How Chatbots Deliver a Superior CX -- 3.5.2 Issues with Chatbots -- 3.6 Conclusion -- References |
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| id | DE-604.BV047804782 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T19:03:25Z |
| indexdate | 2024-07-10T09:21:49Z |
| institution | BVB |
| isbn | 9781000519228 |
| language | English |
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| series2 | Demystifying technologies for computational excellence |
| spelling | Industry 4.0 technologies for business excellence frameworks, practices, and applications edited by Shivani Bali, Sugandha Aggarwal, Sunil Sharma First edition Boca Raton ; London ; New York CRC Press 2022 1 Online-Ressource (xix, 268 Seiten) txt rdacontent c rdamedia cr rdacarrier Demystifying technologies for computational excellence Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editors -- Contributors -- Chapter 1 Understanding the Industry 4.0 Revolution Using Twitter Analytics -- 1.1 Introduction -- 1.2 Literature Review -- 1.3 Methodology -- 1.3.1 Data Collection -- 1.3.2 Data Analysis -- 1.3.2.1 Descriptive Analysis -- 1.3.2.2 Content Analysis -- 1.3.2.3 Network Analysis -- 1.3.2.4 Topic Modeling -- 1.4 Analysis and Results -- 1.4.1 Descriptive Analysis of Tweets -- 1.4.2 CA of Tweets -- 1.4.2.1 Sentiment Analysis of Tweets -- 1.4.2.2 Emotional Scores of Tweets 1.4.3 Network Analytics of Tweets -- 1.4.4 Topic Modeling of Tweets -- 1.5 Discussions -- 1.5.1 The Fourth Industrial Revolution Is Characterized by What Tweets? Can We See Any Particular Patterns of Communication and Information Diffusion in These Tweets? -- 1.5.2 Which Topics and Contents Are Shared in Twitter? Can We Find Any Prevalent Topics or Contents? -- 1.5.3 What Are the Features of Those Users Who Discuss These Topics Related to Industry 4.0 on Twitter? -- 1.5.4 What Sentiments Do These Tweets Contain? What Types of Tweets Tend to Contain Sentiment? -- 1.6 Conclusions 1.6.1 Professional Use of Twitter -- 1.6.2 Organizational Use of Twitter -- 1.6.3 Stakeholder Engagement -- 1.6.4 Hiring -- 1.6.5 Sales Channel -- 1.6.6 Social Listening -- 1.6.7 Risk Management -- 1.7 Limitation and Future Research -- References -- Chapter 2 The Role of Universal Product Coding (UPC), Global Data Synchronization Network (GDSN) and Product Category Management in Efficient Consumer Response (ECR) -- 2.1 Background of ECR -- 2.1.1 ECR as a Profit Center in Supply Chain -- 2.1.2 ECR as a Cost Alleviator in Supply Chain -- 2.1.3 ECR and Operational Efficiency in Supply Chain 2.1.4 ECR as Risk Mitigator in Supply Chain -- 2.1.5 ECR and the Inventory Management in the Supply Chain -- 2.1.6 ECR as a Supply Chain Strategy -- 2.2 Framework of a Global ECR Scorecard -- 2.3 Prerequisite Initiatives for Participation in ECR -- 2.4 Mechanics of ECR -- 2.5 Special Application of ECR in Product Category Management -- 2.6 Universal Product Code (UPC) -- 2.6.1 Features of UPC Barcode -- 2.7 Overview of GDSN -- 2.7.1 Product Information Sharing through GDSN and Impact on ECR -- 2.8 ECR in India -- 2.8.1 An Example of ECR Initiative in India -- 2.8.2 Workgroups in ECR India 2.8.3 The Future of ECR in India -- 2.9 ECR in World -- 2.10 Conclusion -- References -- Chapter 3 Delivering Superior Customer Experience through New-Age Technologies -- 3.1 Introduction -- 3.2 Customer Experience (CX) -- 3.3 Augmented Reality (AR) -- 3.3.1 Impact of AR on CX -- 3.3.2 Industry Examples of Augmented Reality Enhancing CX -- 3.4 Artificial Intelligence (AI) -- 3.4.1 AI in the Domain of CX -- 3.4.2 Industry Examples -- 3.4.3 Issues with AI -- 3.5 Chatbots -- 3.5.1 How Chatbots Deliver a Superior CX -- 3.5.2 Issues with Chatbots -- 3.6 Conclusion -- References Bali, Shivani edt Aggarwal, Sugandha edt Sharma, Sunil edt Erscheint auch als Online-Ausgabe 978-1-003-14047-4 Erscheint auch als Druck-Ausgabe, hbk 978-0-367-69117-2 Erscheint auch als Druck-Ausgabe, pbk 978-0-367-69118-9 |
| spellingShingle | Industry 4.0 technologies for business excellence frameworks, practices, and applications Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editors -- Contributors -- Chapter 1 Understanding the Industry 4.0 Revolution Using Twitter Analytics -- 1.1 Introduction -- 1.2 Literature Review -- 1.3 Methodology -- 1.3.1 Data Collection -- 1.3.2 Data Analysis -- 1.3.2.1 Descriptive Analysis -- 1.3.2.2 Content Analysis -- 1.3.2.3 Network Analysis -- 1.3.2.4 Topic Modeling -- 1.4 Analysis and Results -- 1.4.1 Descriptive Analysis of Tweets -- 1.4.2 CA of Tweets -- 1.4.2.1 Sentiment Analysis of Tweets -- 1.4.2.2 Emotional Scores of Tweets 1.4.3 Network Analytics of Tweets -- 1.4.4 Topic Modeling of Tweets -- 1.5 Discussions -- 1.5.1 The Fourth Industrial Revolution Is Characterized by What Tweets? Can We See Any Particular Patterns of Communication and Information Diffusion in These Tweets? -- 1.5.2 Which Topics and Contents Are Shared in Twitter? Can We Find Any Prevalent Topics or Contents? -- 1.5.3 What Are the Features of Those Users Who Discuss These Topics Related to Industry 4.0 on Twitter? -- 1.5.4 What Sentiments Do These Tweets Contain? What Types of Tweets Tend to Contain Sentiment? -- 1.6 Conclusions 1.6.1 Professional Use of Twitter -- 1.6.2 Organizational Use of Twitter -- 1.6.3 Stakeholder Engagement -- 1.6.4 Hiring -- 1.6.5 Sales Channel -- 1.6.6 Social Listening -- 1.6.7 Risk Management -- 1.7 Limitation and Future Research -- References -- Chapter 2 The Role of Universal Product Coding (UPC), Global Data Synchronization Network (GDSN) and Product Category Management in Efficient Consumer Response (ECR) -- 2.1 Background of ECR -- 2.1.1 ECR as a Profit Center in Supply Chain -- 2.1.2 ECR as a Cost Alleviator in Supply Chain -- 2.1.3 ECR and Operational Efficiency in Supply Chain 2.1.4 ECR as Risk Mitigator in Supply Chain -- 2.1.5 ECR and the Inventory Management in the Supply Chain -- 2.1.6 ECR as a Supply Chain Strategy -- 2.2 Framework of a Global ECR Scorecard -- 2.3 Prerequisite Initiatives for Participation in ECR -- 2.4 Mechanics of ECR -- 2.5 Special Application of ECR in Product Category Management -- 2.6 Universal Product Code (UPC) -- 2.6.1 Features of UPC Barcode -- 2.7 Overview of GDSN -- 2.7.1 Product Information Sharing through GDSN and Impact on ECR -- 2.8 ECR in India -- 2.8.1 An Example of ECR Initiative in India -- 2.8.2 Workgroups in ECR India 2.8.3 The Future of ECR in India -- 2.9 ECR in World -- 2.10 Conclusion -- References -- Chapter 3 Delivering Superior Customer Experience through New-Age Technologies -- 3.1 Introduction -- 3.2 Customer Experience (CX) -- 3.3 Augmented Reality (AR) -- 3.3.1 Impact of AR on CX -- 3.3.2 Industry Examples of Augmented Reality Enhancing CX -- 3.4 Artificial Intelligence (AI) -- 3.4.1 AI in the Domain of CX -- 3.4.2 Industry Examples -- 3.4.3 Issues with AI -- 3.5 Chatbots -- 3.5.1 How Chatbots Deliver a Superior CX -- 3.5.2 Issues with Chatbots -- 3.6 Conclusion -- References |
| title | Industry 4.0 technologies for business excellence frameworks, practices, and applications |
| title_auth | Industry 4.0 technologies for business excellence frameworks, practices, and applications |
| title_exact_search | Industry 4.0 technologies for business excellence frameworks, practices, and applications |
| title_exact_search_txtP | Industry 4.0 technologies for business excellence frameworks, practices, and applications |
| title_full | Industry 4.0 technologies for business excellence frameworks, practices, and applications edited by Shivani Bali, Sugandha Aggarwal, Sunil Sharma |
| title_fullStr | Industry 4.0 technologies for business excellence frameworks, practices, and applications edited by Shivani Bali, Sugandha Aggarwal, Sunil Sharma |
| title_full_unstemmed | Industry 4.0 technologies for business excellence frameworks, practices, and applications edited by Shivani Bali, Sugandha Aggarwal, Sunil Sharma |
| title_short | Industry 4.0 technologies for business excellence |
| title_sort | industry 4 0 technologies for business excellence frameworks practices and applications |
| title_sub | frameworks, practices, and applications |
| work_keys_str_mv | AT balishivani industry40technologiesforbusinessexcellenceframeworkspracticesandapplications AT aggarwalsugandha industry40technologiesforbusinessexcellenceframeworkspracticesandapplications AT sharmasunil industry40technologiesforbusinessexcellenceframeworkspracticesandapplications |