Strategic System Assurance and Business Analytics:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Singapore
Springer Singapore Pte. Limited
2020
|
| Series: | Asset Analytics Ser
|
| Subjects: | |
| Links: | https://ebookcentral.proquest.com/lib/hwr/detail.action?docID=6232198 |
| Item Description: | Description based on publisher supplied metadata and other sources |
| Physical Description: | 1 Online-Ressource (603 pages) |
| ISBN: | 9789811536472 |
Staff View
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| 505 | 8 | |a Intro -- Preface -- Acknowledgements -- Contents -- Editors and Contributors -- 1 Investing Data with Machine Learning Using Python -- 1.1 Introduction -- 1.2 Supervised and Unsupervised Machine Learning -- 1.3 Word Done -- 1.3.1 Data Extraction -- 1.3.2 Data Analysis -- 1.3.3 Predictions -- 1.4 Conclusion -- References -- 2 Probabilistic Assessment of Complex System with Two Subsystems in Series Arrangement with Multi-types Failure and Two Types of Repair Using Copula -- 2.1 Introduction -- 2.1.1 State Description -- 2.1.2 Assumptions -- 2.1.3 Notations -- 2.1.4 System Configuration and State Transition Diagram -- 2.2 Mathematical Formulation of the Model -- 2.2.1 Solution of the Model -- 2.3 Analytical Study of the Model for the Particular Case -- 2.4 Result Analysis and Conclusions -- References -- 3 Recognition and Optimizing Process Lagging Indicators During Software Development -- 3.1 Introduction [1] -- 3.2 Major Challenges Faced in Software Development [2] -- 3.3 Equilibrium Between Project Constraints [2, 3] -- 3.3.1 Selection of Triple Constraints [4] -- 3.4 Recognition of Relevant Process Lagging and Leading Indicators [3, 5] -- 3.4.1 Customer Requirement -- 3.4.2 Project Agreement -- 3.4.3 Type of Project -- 3.4.4 Phase of Project -- 3.4.5 Organization Business Goal -- 3.4.6 Recognition of Leading Indicators -- 3.5 Monitoring of Process Lagging and Leading Indicators [3, 6] -- 3.6 Optimization of Process Lagging and Leading Indicators [6] -- 3.7 Conclusion -- References -- 4 Risk and Safety Analysis of Warships Operational Lifetime Defects -- 4.1 Introduction -- 4.2 Warship Design Cycle -- 4.2.1 Warship Design Production and Operation Lifecycle -- 4.2.2 Warship Design Production and Operation Lifecycle-Risks and Mitigation Regime -- 4.2.3 Warship-Systems Approach -- 4.3 Case Study -- 4.3.1 Methodology of Study | |
| 505 | 8 | |a 4.3.2 Risk Calculation -- 4.3.3 The Analysis -- 4.4 The Conclusion -- 4.5 Way Ahead -- References -- 5 Facebook Data Breach: A Systematic Review of Its Consequences on Consumers' Behaviour Towards Advertising -- 5.1 Introduction -- 5.1.1 Applications as a Tool for Data Breach -- 5.1.2 Facebook-Cambridge Analytical Privacy Breach -- 5.1.3 Consequences of Privacy Failure -- 5.1.4 Research Problem and Objectives -- 5.2 Methodology -- 5.3 Literature Review and Theoretical Development -- 5.3.1 The Concept of Privacy -- 5.3.2 Theoretical Perspectives of Data Breach -- 5.3.3 Social Networking Sites Advertising and Informational Privacy -- 5.3.4 Privacy Concerns and Online Consumers Behaviour -- 5.3.5 Trust and Online Consumer Behaviour -- 5.3.6 Consumers' Online Data Protection -- 5.4 Research Model and Hypotheses -- 5.4.1 Perceived Data Breach -- 5.4.2 Privacy Concerns -- 5.4.3 Trust -- 5.4.4 Emotional Violation -- 5.4.5 Ad Behaviour -- 5.5 Discussion and Implications -- 5.6 Conclusion, Limitations and Scope for Further Research -- References -- 6 Fuzzy DEMATEL Approach to Identify the Factors Influencing Efficiency of Indian Retail Websites -- 6.1 Introduction -- 6.2 Objective -- 6.3 Methodology -- 6.3.1 Fuzzy DEMATEL Approach -- 6.4 Numerical Interpretation -- 6.5 Conclusion -- References -- 7 Application of Statistical Techniques in Project Monitoring and Control -- 7.1 Introduction -- 7.2 Major Challenges in Project Execution and Data Collection [1] -- 7.3 Life Cycle of Metric Data Collection and Analysis -- 7.3.1 Project Data Collection Method -- 7.4 Creation of Process Performance Baseline and Models [2] -- 7.4.1 Process Performance Baseline Creation [3] -- 7.4.2 Process Performance Model Creation -- 7.5 Application of Statistical Techniques in Project Monitoring and Control -- 7.5.1 What-if Analysis [4] -- 7.5.2 Causal Analysis and Resolution (CAR) | |
| 505 | 8 | |a 7.6 How to Measure Improvements in Projects [5] -- 7.6.1 Two Sample T-Test -- 7.6.2 Two Sample F-Tests -- 7.7 Conclusion -- References -- 8 Sensor-Based Smart Agriculture in India -- 8.1 Introduction -- 8.1.1 Drone Technology -- 8.2 Literature Review -- 8.2.1 Drones in Indian Agriculture -- 8.3 Research Objective -- 8.4 Research Methodology -- 8.5 Findings -- 8.5.1 Drones for Farmers -- 8.5.2 Sensor-Based Technology Used for Agriculture in Some Experiments -- 8.6 Recommendations -- 8.7 Significance of the Study -- References -- 9 Integrating UTAUT with Trust and Perceived Benefits to Explain User Adoption of Mobile Payments -- 9.1 Introduction and Literature Review -- 9.2 Hypothesis and Model Development -- 9.2.1 Unified Theory of Acceptance and Use of Technology (UTAUT) -- 9.2.2 Perceived Benefits (PBN) -- 9.2.3 Trust -- 9.3 Research Methodology -- 9.3.1 Research Design and Research Method -- 9.3.2 Survey Location and Target Respondents -- 9.3.3 Questionnaire Design -- 9.4 Results of the Study -- 9.4.1 Sample Profile -- 9.4.2 Validity and Reliability -- 9.4.3 Model Testing -- 9.5 Discussion and Conclusion -- 9.6 Limitations of the Study and Future Scope -- References -- 10 Improving the Quality of Customer Service of Financial Institutions: The Implementation of Challenger Banks -- 10.1 Introduction -- 10.2 Key Research Findings -- 10.2.1 Ways to Improve the Quality of Customer Service in Financial Institutions -- 10.2.2 Challenger Banks-A New Form of Customer Service -- 10.2.3 Efficiency Evaluation of Challenger Banks -- 10.3 Result of Modeling -- 10.4 Conclusions -- References -- 11 Corporate Image Building in the Indian IT Sector: Conceptualizing Through HR Practices -- 11.1 Introduction -- 11.1.1 Corporate Image -- 11.1.2 Employees and HR Practices -- 11.2 Literature Survey -- 11.2.1 Research Strategy | |
| 505 | 8 | |a 11.2.2 Corporate Image Building: Conceptual Perspectives -- 11.2.3 HR Practices -- 11.2.4 Employer Branding -- 11.2.5 Corporate Social Responsibility -- 11.2.6 Corporate Social Performance -- 11.3 Methodology -- 11.4 Results and Discussion -- 11.5 Conclusion -- 11.6 Future Scope -- References -- 12 Vague Reliability Analysis of Standby Systems with an (N + 1) Units -- 12.1 Introduction -- 12.2 Notations -- 12.3 Model Description -- 12.4 Mathematical Formulation of the Model -- 12.5 Solution of the Model -- 12.6 Vague Reliability Analysis of the Model -- 12.7 Discussion and Interpretation -- References -- 13 Experimental Study for MRR and TWR on Machining of Inconel 718 using ZNC EDM -- 13.1 Introduction -- 13.2 Literature Survey -- 13.3 Methodology -- 13.4 Results and Discussion -- 13.5 Effect of Factors on MRR and TWR -- 13.6 Conclusions -- 13.7 Future Scope -- References -- 14 Blind Quantitative Steganalysis Using CNN-Long Short-Term Memory Architecture -- 14.1 Introduction -- 14.2 Related Work -- 14.3 Background Concepts -- 14.3.1 Convolutional Neural Networks -- 14.3.2 Long Short-Term Memory Network -- 14.3.3 CNN with LSTM -- 14.3.4 Dense and Dropout Layer -- 14.3.5 Mean Absolute Error -- 14.4 Proposed Framework -- 14.5 Experimental Study -- 14.6 Conclusions -- References -- 15 Performance of Autoregressive Tree Model in Forecasting Cancer Patients -- 15.1 Introduction -- 15.2 Source of Data -- 15.3 Methodology -- 15.4 Result and Discussion -- 15.4.1 Fitted AR Model -- 15.4.2 Fitted ART Model -- 15.4.3 Forecast Trend of Type of Cancer -- 15.4.4 Model Forecasting Comparison -- 15.4.5 Hypothesis Testing -- 15.5 Conclusion -- 15.6 Future Scope -- References -- 16 Developing a Usage Space Dimension Model to Investigate Influence of Intention to Use on Actual Usage of Mobile Phones -- 16.1 Introduction -- 16.2 Literature Review | |
| 505 | 8 | |a 16.2.1 Mobile Use Practices Among Professionals -- 16.2.2 The UTAUT Model -- 16.2.3 Usage Spaces -- 16.3 Research Gap -- 16.3.1 Purpose of the Study -- 16.4 Research Methodology -- 16.4.1 Data Collection and Survey Procedure -- 16.5 Data Analysis and Results -- 16.5.1 Demographics -- 16.5.2 Individual Mobile Use -- 16.5.3 Reported Usage -- 16.5.4 Reliability Analysis -- 16.5.5 Validity Analysis -- 16.5.6 Confirmatory Factor Analysis -- 16.5.7 Effect of Gender on IE and AU Across the Usage Space Dimensions -- 16.5.8 Effect of Age on IE and AU Across the Usage Space Dimensions -- 16.5.9 Discussions and Conclusions -- 16.6 Limitations, Implications, and Future Research -- Appendix: Reported Usage Across Usage Space Dimensions -- References -- 17 Examining the Relationship Between Customer-Oriented Success Factors, Customer Satisfaction, and Repurchase Intention for Mobile Commerce -- 17.1 Introduction -- 17.2 Related Work and Hypotheses Development -- 17.2.1 M-Commerce Application Success (MAS) -- 17.2.2 Customer Satisfaction (CS) -- 17.2.3 Repurchase Intention (RI) -- 17.3 Methodology -- 17.4 Data Analysis Summary -- 17.4.1 Demographic Profile of the Respondents -- 17.4.2 Validity and Reliability of Measures -- 17.4.3 SEM Results -- 17.5 Discussions and Conclusions -- Appendix -- References -- 18 Smart Industrial Packaging and Sorting System -- 18.1 Introduction -- 18.2 Conventional System -- 18.2.1 Mechanical Arms -- 18.2.2 Hand-Based Sorting System -- 18.2.3 Shape-Based Sorting System -- 18.3 Proposed System Modelling with Flow Chart -- 18.4 Product Specification for Proposed Model -- 18.5 Technical Aspect and Interfacing in the Model -- 18.6 Result -- 18.7 Conclusion -- References -- 19 Credentials Safety and System Security Pay-off and Trade-off: Comfort Level Security Assurance Framework -- 19.1 Introduction -- 19.2 Background | |
| 505 | 8 | |a 19.3 Right Functionality | |
| 650 | 4 | |a Management information systems | |
| 700 | 1 | |a Singh, Ompal |e Sonstige |4 oth | |
| 700 | 1 | |a Khatri, Sunil Kumar |e Sonstige |4 oth | |
| 700 | 1 | |a Verma, Ajit Kumar |e Sonstige |4 oth | |
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Record in the Search Index
| _version_ | 1818989467451523072 |
|---|---|
| any_adam_object | |
| author | Kapur, P. K. |
| author_facet | Kapur, P. K. |
| author_role | aut |
| author_sort | Kapur, P. K. |
| author_variant | p k k pk pkk |
| building | Verbundindex |
| bvnumber | BV048222885 |
| collection | ZDB-30-PQE |
| contents | Intro -- Preface -- Acknowledgements -- Contents -- Editors and Contributors -- 1 Investing Data with Machine Learning Using Python -- 1.1 Introduction -- 1.2 Supervised and Unsupervised Machine Learning -- 1.3 Word Done -- 1.3.1 Data Extraction -- 1.3.2 Data Analysis -- 1.3.3 Predictions -- 1.4 Conclusion -- References -- 2 Probabilistic Assessment of Complex System with Two Subsystems in Series Arrangement with Multi-types Failure and Two Types of Repair Using Copula -- 2.1 Introduction -- 2.1.1 State Description -- 2.1.2 Assumptions -- 2.1.3 Notations -- 2.1.4 System Configuration and State Transition Diagram -- 2.2 Mathematical Formulation of the Model -- 2.2.1 Solution of the Model -- 2.3 Analytical Study of the Model for the Particular Case -- 2.4 Result Analysis and Conclusions -- References -- 3 Recognition and Optimizing Process Lagging Indicators During Software Development -- 3.1 Introduction [1] -- 3.2 Major Challenges Faced in Software Development [2] -- 3.3 Equilibrium Between Project Constraints [2, 3] -- 3.3.1 Selection of Triple Constraints [4] -- 3.4 Recognition of Relevant Process Lagging and Leading Indicators [3, 5] -- 3.4.1 Customer Requirement -- 3.4.2 Project Agreement -- 3.4.3 Type of Project -- 3.4.4 Phase of Project -- 3.4.5 Organization Business Goal -- 3.4.6 Recognition of Leading Indicators -- 3.5 Monitoring of Process Lagging and Leading Indicators [3, 6] -- 3.6 Optimization of Process Lagging and Leading Indicators [6] -- 3.7 Conclusion -- References -- 4 Risk and Safety Analysis of Warships Operational Lifetime Defects -- 4.1 Introduction -- 4.2 Warship Design Cycle -- 4.2.1 Warship Design Production and Operation Lifecycle -- 4.2.2 Warship Design Production and Operation Lifecycle-Risks and Mitigation Regime -- 4.2.3 Warship-Systems Approach -- 4.3 Case Study -- 4.3.1 Methodology of Study 4.3.2 Risk Calculation -- 4.3.3 The Analysis -- 4.4 The Conclusion -- 4.5 Way Ahead -- References -- 5 Facebook Data Breach: A Systematic Review of Its Consequences on Consumers' Behaviour Towards Advertising -- 5.1 Introduction -- 5.1.1 Applications as a Tool for Data Breach -- 5.1.2 Facebook-Cambridge Analytical Privacy Breach -- 5.1.3 Consequences of Privacy Failure -- 5.1.4 Research Problem and Objectives -- 5.2 Methodology -- 5.3 Literature Review and Theoretical Development -- 5.3.1 The Concept of Privacy -- 5.3.2 Theoretical Perspectives of Data Breach -- 5.3.3 Social Networking Sites Advertising and Informational Privacy -- 5.3.4 Privacy Concerns and Online Consumers Behaviour -- 5.3.5 Trust and Online Consumer Behaviour -- 5.3.6 Consumers' Online Data Protection -- 5.4 Research Model and Hypotheses -- 5.4.1 Perceived Data Breach -- 5.4.2 Privacy Concerns -- 5.4.3 Trust -- 5.4.4 Emotional Violation -- 5.4.5 Ad Behaviour -- 5.5 Discussion and Implications -- 5.6 Conclusion, Limitations and Scope for Further Research -- References -- 6 Fuzzy DEMATEL Approach to Identify the Factors Influencing Efficiency of Indian Retail Websites -- 6.1 Introduction -- 6.2 Objective -- 6.3 Methodology -- 6.3.1 Fuzzy DEMATEL Approach -- 6.4 Numerical Interpretation -- 6.5 Conclusion -- References -- 7 Application of Statistical Techniques in Project Monitoring and Control -- 7.1 Introduction -- 7.2 Major Challenges in Project Execution and Data Collection [1] -- 7.3 Life Cycle of Metric Data Collection and Analysis -- 7.3.1 Project Data Collection Method -- 7.4 Creation of Process Performance Baseline and Models [2] -- 7.4.1 Process Performance Baseline Creation [3] -- 7.4.2 Process Performance Model Creation -- 7.5 Application of Statistical Techniques in Project Monitoring and Control -- 7.5.1 What-if Analysis [4] -- 7.5.2 Causal Analysis and Resolution (CAR) 7.6 How to Measure Improvements in Projects [5] -- 7.6.1 Two Sample T-Test -- 7.6.2 Two Sample F-Tests -- 7.7 Conclusion -- References -- 8 Sensor-Based Smart Agriculture in India -- 8.1 Introduction -- 8.1.1 Drone Technology -- 8.2 Literature Review -- 8.2.1 Drones in Indian Agriculture -- 8.3 Research Objective -- 8.4 Research Methodology -- 8.5 Findings -- 8.5.1 Drones for Farmers -- 8.5.2 Sensor-Based Technology Used for Agriculture in Some Experiments -- 8.6 Recommendations -- 8.7 Significance of the Study -- References -- 9 Integrating UTAUT with Trust and Perceived Benefits to Explain User Adoption of Mobile Payments -- 9.1 Introduction and Literature Review -- 9.2 Hypothesis and Model Development -- 9.2.1 Unified Theory of Acceptance and Use of Technology (UTAUT) -- 9.2.2 Perceived Benefits (PBN) -- 9.2.3 Trust -- 9.3 Research Methodology -- 9.3.1 Research Design and Research Method -- 9.3.2 Survey Location and Target Respondents -- 9.3.3 Questionnaire Design -- 9.4 Results of the Study -- 9.4.1 Sample Profile -- 9.4.2 Validity and Reliability -- 9.4.3 Model Testing -- 9.5 Discussion and Conclusion -- 9.6 Limitations of the Study and Future Scope -- References -- 10 Improving the Quality of Customer Service of Financial Institutions: The Implementation of Challenger Banks -- 10.1 Introduction -- 10.2 Key Research Findings -- 10.2.1 Ways to Improve the Quality of Customer Service in Financial Institutions -- 10.2.2 Challenger Banks-A New Form of Customer Service -- 10.2.3 Efficiency Evaluation of Challenger Banks -- 10.3 Result of Modeling -- 10.4 Conclusions -- References -- 11 Corporate Image Building in the Indian IT Sector: Conceptualizing Through HR Practices -- 11.1 Introduction -- 11.1.1 Corporate Image -- 11.1.2 Employees and HR Practices -- 11.2 Literature Survey -- 11.2.1 Research Strategy 11.2.2 Corporate Image Building: Conceptual Perspectives -- 11.2.3 HR Practices -- 11.2.4 Employer Branding -- 11.2.5 Corporate Social Responsibility -- 11.2.6 Corporate Social Performance -- 11.3 Methodology -- 11.4 Results and Discussion -- 11.5 Conclusion -- 11.6 Future Scope -- References -- 12 Vague Reliability Analysis of Standby Systems with an (N + 1) Units -- 12.1 Introduction -- 12.2 Notations -- 12.3 Model Description -- 12.4 Mathematical Formulation of the Model -- 12.5 Solution of the Model -- 12.6 Vague Reliability Analysis of the Model -- 12.7 Discussion and Interpretation -- References -- 13 Experimental Study for MRR and TWR on Machining of Inconel 718 using ZNC EDM -- 13.1 Introduction -- 13.2 Literature Survey -- 13.3 Methodology -- 13.4 Results and Discussion -- 13.5 Effect of Factors on MRR and TWR -- 13.6 Conclusions -- 13.7 Future Scope -- References -- 14 Blind Quantitative Steganalysis Using CNN-Long Short-Term Memory Architecture -- 14.1 Introduction -- 14.2 Related Work -- 14.3 Background Concepts -- 14.3.1 Convolutional Neural Networks -- 14.3.2 Long Short-Term Memory Network -- 14.3.3 CNN with LSTM -- 14.3.4 Dense and Dropout Layer -- 14.3.5 Mean Absolute Error -- 14.4 Proposed Framework -- 14.5 Experimental Study -- 14.6 Conclusions -- References -- 15 Performance of Autoregressive Tree Model in Forecasting Cancer Patients -- 15.1 Introduction -- 15.2 Source of Data -- 15.3 Methodology -- 15.4 Result and Discussion -- 15.4.1 Fitted AR Model -- 15.4.2 Fitted ART Model -- 15.4.3 Forecast Trend of Type of Cancer -- 15.4.4 Model Forecasting Comparison -- 15.4.5 Hypothesis Testing -- 15.5 Conclusion -- 15.6 Future Scope -- References -- 16 Developing a Usage Space Dimension Model to Investigate Influence of Intention to Use on Actual Usage of Mobile Phones -- 16.1 Introduction -- 16.2 Literature Review 16.2.1 Mobile Use Practices Among Professionals -- 16.2.2 The UTAUT Model -- 16.2.3 Usage Spaces -- 16.3 Research Gap -- 16.3.1 Purpose of the Study -- 16.4 Research Methodology -- 16.4.1 Data Collection and Survey Procedure -- 16.5 Data Analysis and Results -- 16.5.1 Demographics -- 16.5.2 Individual Mobile Use -- 16.5.3 Reported Usage -- 16.5.4 Reliability Analysis -- 16.5.5 Validity Analysis -- 16.5.6 Confirmatory Factor Analysis -- 16.5.7 Effect of Gender on IE and AU Across the Usage Space Dimensions -- 16.5.8 Effect of Age on IE and AU Across the Usage Space Dimensions -- 16.5.9 Discussions and Conclusions -- 16.6 Limitations, Implications, and Future Research -- Appendix: Reported Usage Across Usage Space Dimensions -- References -- 17 Examining the Relationship Between Customer-Oriented Success Factors, Customer Satisfaction, and Repurchase Intention for Mobile Commerce -- 17.1 Introduction -- 17.2 Related Work and Hypotheses Development -- 17.2.1 M-Commerce Application Success (MAS) -- 17.2.2 Customer Satisfaction (CS) -- 17.2.3 Repurchase Intention (RI) -- 17.3 Methodology -- 17.4 Data Analysis Summary -- 17.4.1 Demographic Profile of the Respondents -- 17.4.2 Validity and Reliability of Measures -- 17.4.3 SEM Results -- 17.5 Discussions and Conclusions -- Appendix -- References -- 18 Smart Industrial Packaging and Sorting System -- 18.1 Introduction -- 18.2 Conventional System -- 18.2.1 Mechanical Arms -- 18.2.2 Hand-Based Sorting System -- 18.2.3 Shape-Based Sorting System -- 18.3 Proposed System Modelling with Flow Chart -- 18.4 Product Specification for Proposed Model -- 18.5 Technical Aspect and Interfacing in the Model -- 18.6 Result -- 18.7 Conclusion -- References -- 19 Credentials Safety and System Security Pay-off and Trade-off: Comfort Level Security Assurance Framework -- 19.1 Introduction -- 19.2 Background 19.3 Right Functionality |
| ctrlnum | (ZDB-30-PQE)EBC6232198 (ZDB-30-PAD)EBC6232198 (ZDB-89-EBL)EBL6232198 (OCoLC)1162256890 (DE-599)BVBBV048222885 |
| dewey-full | 658.4038011 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.4038011 |
| dewey-search | 658.4038011 |
| dewey-sort | 3658.4038011 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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Constraints [4] -- 3.4 Recognition of Relevant Process Lagging and Leading Indicators [3, 5] -- 3.4.1 Customer Requirement -- 3.4.2 Project Agreement -- 3.4.3 Type of Project -- 3.4.4 Phase of Project -- 3.4.5 Organization Business Goal -- 3.4.6 Recognition of Leading Indicators -- 3.5 Monitoring of Process Lagging and Leading Indicators [3, 6] -- 3.6 Optimization of Process Lagging and Leading Indicators [6] -- 3.7 Conclusion -- References -- 4 Risk and Safety Analysis of Warships Operational Lifetime Defects -- 4.1 Introduction -- 4.2 Warship Design Cycle -- 4.2.1 Warship Design Production and Operation Lifecycle -- 4.2.2 Warship Design Production and Operation Lifecycle-Risks and Mitigation Regime -- 4.2.3 Warship-Systems Approach -- 4.3 Case Study -- 4.3.1 Methodology of Study</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">4.3.2 Risk Calculation -- 4.3.3 The Analysis -- 4.4 The Conclusion -- 4.5 Way Ahead -- References -- 5 Facebook Data Breach: A Systematic Review of Its Consequences on Consumers' Behaviour Towards Advertising -- 5.1 Introduction -- 5.1.1 Applications as a Tool for Data Breach -- 5.1.2 Facebook-Cambridge Analytical Privacy Breach -- 5.1.3 Consequences of Privacy Failure -- 5.1.4 Research Problem and Objectives -- 5.2 Methodology -- 5.3 Literature Review and Theoretical Development -- 5.3.1 The Concept of Privacy -- 5.3.2 Theoretical Perspectives of Data Breach -- 5.3.3 Social Networking Sites Advertising and Informational Privacy -- 5.3.4 Privacy Concerns and Online Consumers Behaviour -- 5.3.5 Trust and Online Consumer Behaviour -- 5.3.6 Consumers' Online Data Protection -- 5.4 Research Model and Hypotheses -- 5.4.1 Perceived Data Breach -- 5.4.2 Privacy Concerns -- 5.4.3 Trust -- 5.4.4 Emotional Violation -- 5.4.5 Ad Behaviour -- 5.5 Discussion and Implications -- 5.6 Conclusion, Limitations and Scope for Further Research -- References -- 6 Fuzzy DEMATEL Approach to Identify the Factors Influencing Efficiency of Indian Retail Websites -- 6.1 Introduction -- 6.2 Objective -- 6.3 Methodology -- 6.3.1 Fuzzy DEMATEL Approach -- 6.4 Numerical Interpretation -- 6.5 Conclusion -- References -- 7 Application of Statistical Techniques in Project Monitoring and Control -- 7.1 Introduction -- 7.2 Major Challenges in Project Execution and Data Collection [1] -- 7.3 Life Cycle of Metric Data Collection and Analysis -- 7.3.1 Project Data Collection Method -- 7.4 Creation of Process Performance Baseline and Models [2] -- 7.4.1 Process Performance Baseline Creation [3] -- 7.4.2 Process Performance Model Creation -- 7.5 Application of Statistical Techniques in Project Monitoring and Control -- 7.5.1 What-if Analysis [4] -- 7.5.2 Causal Analysis and Resolution (CAR)</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">7.6 How to Measure Improvements in Projects [5] -- 7.6.1 Two Sample T-Test -- 7.6.2 Two Sample F-Tests -- 7.7 Conclusion -- References -- 8 Sensor-Based Smart Agriculture in India -- 8.1 Introduction -- 8.1.1 Drone Technology -- 8.2 Literature Review -- 8.2.1 Drones in Indian Agriculture -- 8.3 Research Objective -- 8.4 Research Methodology -- 8.5 Findings -- 8.5.1 Drones for Farmers -- 8.5.2 Sensor-Based Technology Used for Agriculture in Some Experiments -- 8.6 Recommendations -- 8.7 Significance of the Study -- References -- 9 Integrating UTAUT with Trust and Perceived Benefits to Explain User Adoption of Mobile Payments -- 9.1 Introduction and Literature Review -- 9.2 Hypothesis and Model Development -- 9.2.1 Unified Theory of Acceptance and Use of Technology (UTAUT) -- 9.2.2 Perceived Benefits (PBN) -- 9.2.3 Trust -- 9.3 Research Methodology -- 9.3.1 Research Design and Research Method -- 9.3.2 Survey Location and Target Respondents -- 9.3.3 Questionnaire Design -- 9.4 Results of the Study -- 9.4.1 Sample Profile -- 9.4.2 Validity and Reliability -- 9.4.3 Model Testing -- 9.5 Discussion and Conclusion -- 9.6 Limitations of the Study and Future Scope -- References -- 10 Improving the Quality of Customer Service of Financial Institutions: The Implementation of Challenger Banks -- 10.1 Introduction -- 10.2 Key Research Findings -- 10.2.1 Ways to Improve the Quality of Customer Service in Financial Institutions -- 10.2.2 Challenger Banks-A New Form of Customer Service -- 10.2.3 Efficiency Evaluation of Challenger Banks -- 10.3 Result of Modeling -- 10.4 Conclusions -- References -- 11 Corporate Image Building in the Indian IT Sector: Conceptualizing Through HR Practices -- 11.1 Introduction -- 11.1.1 Corporate Image -- 11.1.2 Employees and HR Practices -- 11.2 Literature Survey -- 11.2.1 Research Strategy</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">11.2.2 Corporate Image Building: Conceptual Perspectives -- 11.2.3 HR Practices -- 11.2.4 Employer Branding -- 11.2.5 Corporate Social Responsibility -- 11.2.6 Corporate Social Performance -- 11.3 Methodology -- 11.4 Results and Discussion -- 11.5 Conclusion -- 11.6 Future Scope -- References -- 12 Vague Reliability Analysis of Standby Systems with an (N + 1) Units -- 12.1 Introduction -- 12.2 Notations -- 12.3 Model Description -- 12.4 Mathematical Formulation of the Model -- 12.5 Solution of the Model -- 12.6 Vague Reliability Analysis of the Model -- 12.7 Discussion and Interpretation -- References -- 13 Experimental Study for MRR and TWR on Machining of Inconel 718 using ZNC EDM -- 13.1 Introduction -- 13.2 Literature Survey -- 13.3 Methodology -- 13.4 Results and Discussion -- 13.5 Effect of Factors on MRR and TWR -- 13.6 Conclusions -- 13.7 Future Scope -- References -- 14 Blind Quantitative Steganalysis Using CNN-Long Short-Term Memory Architecture -- 14.1 Introduction -- 14.2 Related Work -- 14.3 Background Concepts -- 14.3.1 Convolutional Neural Networks -- 14.3.2 Long Short-Term Memory Network -- 14.3.3 CNN with LSTM -- 14.3.4 Dense and Dropout Layer -- 14.3.5 Mean Absolute Error -- 14.4 Proposed Framework -- 14.5 Experimental Study -- 14.6 Conclusions -- References -- 15 Performance of Autoregressive Tree Model in Forecasting Cancer Patients -- 15.1 Introduction -- 15.2 Source of Data -- 15.3 Methodology -- 15.4 Result and Discussion -- 15.4.1 Fitted AR Model -- 15.4.2 Fitted ART Model -- 15.4.3 Forecast Trend of Type of Cancer -- 15.4.4 Model Forecasting Comparison -- 15.4.5 Hypothesis Testing -- 15.5 Conclusion -- 15.6 Future Scope -- References -- 16 Developing a Usage Space Dimension Model to Investigate Influence of Intention to Use on Actual Usage of Mobile Phones -- 16.1 Introduction -- 16.2 Literature Review</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">16.2.1 Mobile Use Practices Among Professionals -- 16.2.2 The UTAUT Model -- 16.2.3 Usage Spaces -- 16.3 Research Gap -- 16.3.1 Purpose of the Study -- 16.4 Research Methodology -- 16.4.1 Data Collection and Survey Procedure -- 16.5 Data Analysis and Results -- 16.5.1 Demographics -- 16.5.2 Individual Mobile Use -- 16.5.3 Reported Usage -- 16.5.4 Reliability Analysis -- 16.5.5 Validity Analysis -- 16.5.6 Confirmatory Factor Analysis -- 16.5.7 Effect of Gender on IE and AU Across the Usage Space Dimensions -- 16.5.8 Effect of Age on IE and AU Across the Usage Space Dimensions -- 16.5.9 Discussions and Conclusions -- 16.6 Limitations, Implications, and Future Research -- Appendix: Reported Usage Across Usage Space Dimensions -- References -- 17 Examining the Relationship Between Customer-Oriented Success Factors, Customer Satisfaction, and Repurchase Intention for Mobile Commerce -- 17.1 Introduction -- 17.2 Related Work and Hypotheses Development -- 17.2.1 M-Commerce Application Success (MAS) -- 17.2.2 Customer Satisfaction (CS) -- 17.2.3 Repurchase Intention (RI) -- 17.3 Methodology -- 17.4 Data Analysis Summary -- 17.4.1 Demographic Profile of the Respondents -- 17.4.2 Validity and Reliability of Measures -- 17.4.3 SEM Results -- 17.5 Discussions and Conclusions -- Appendix -- References -- 18 Smart Industrial Packaging and Sorting System -- 18.1 Introduction -- 18.2 Conventional System -- 18.2.1 Mechanical Arms -- 18.2.2 Hand-Based Sorting System -- 18.2.3 Shape-Based Sorting System -- 18.3 Proposed System Modelling with Flow Chart -- 18.4 Product Specification for Proposed Model -- 18.5 Technical Aspect and Interfacing in the Model -- 18.6 Result -- 18.7 Conclusion -- References -- 19 Credentials Safety and System Security Pay-off and Trade-off: Comfort Level Security Assurance Framework -- 19.1 Introduction -- 19.2 Background</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">19.3 Right Functionality</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Management information systems</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Singh, Ompal</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" 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| id | DE-604.BV048222885 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T19:38:56Z |
| institution | BVB |
| isbn | 9789811536472 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033603618 |
| oclc_num | 1162256890 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (603 pages) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Springer Singapore Pte. Limited |
| record_format | marc |
| series2 | Asset Analytics Ser |
| spelling | Kapur, P. K. Verfasser aut Strategic System Assurance and Business Analytics Singapore Springer Singapore Pte. Limited 2020 ©2020 1 Online-Ressource (603 pages) txt rdacontent c rdamedia cr rdacarrier Asset Analytics Ser Description based on publisher supplied metadata and other sources Intro -- Preface -- Acknowledgements -- Contents -- Editors and Contributors -- 1 Investing Data with Machine Learning Using Python -- 1.1 Introduction -- 1.2 Supervised and Unsupervised Machine Learning -- 1.3 Word Done -- 1.3.1 Data Extraction -- 1.3.2 Data Analysis -- 1.3.3 Predictions -- 1.4 Conclusion -- References -- 2 Probabilistic Assessment of Complex System with Two Subsystems in Series Arrangement with Multi-types Failure and Two Types of Repair Using Copula -- 2.1 Introduction -- 2.1.1 State Description -- 2.1.2 Assumptions -- 2.1.3 Notations -- 2.1.4 System Configuration and State Transition Diagram -- 2.2 Mathematical Formulation of the Model -- 2.2.1 Solution of the Model -- 2.3 Analytical Study of the Model for the Particular Case -- 2.4 Result Analysis and Conclusions -- References -- 3 Recognition and Optimizing Process Lagging Indicators During Software Development -- 3.1 Introduction [1] -- 3.2 Major Challenges Faced in Software Development [2] -- 3.3 Equilibrium Between Project Constraints [2, 3] -- 3.3.1 Selection of Triple Constraints [4] -- 3.4 Recognition of Relevant Process Lagging and Leading Indicators [3, 5] -- 3.4.1 Customer Requirement -- 3.4.2 Project Agreement -- 3.4.3 Type of Project -- 3.4.4 Phase of Project -- 3.4.5 Organization Business Goal -- 3.4.6 Recognition of Leading Indicators -- 3.5 Monitoring of Process Lagging and Leading Indicators [3, 6] -- 3.6 Optimization of Process Lagging and Leading Indicators [6] -- 3.7 Conclusion -- References -- 4 Risk and Safety Analysis of Warships Operational Lifetime Defects -- 4.1 Introduction -- 4.2 Warship Design Cycle -- 4.2.1 Warship Design Production and Operation Lifecycle -- 4.2.2 Warship Design Production and Operation Lifecycle-Risks and Mitigation Regime -- 4.2.3 Warship-Systems Approach -- 4.3 Case Study -- 4.3.1 Methodology of Study 4.3.2 Risk Calculation -- 4.3.3 The Analysis -- 4.4 The Conclusion -- 4.5 Way Ahead -- References -- 5 Facebook Data Breach: A Systematic Review of Its Consequences on Consumers' Behaviour Towards Advertising -- 5.1 Introduction -- 5.1.1 Applications as a Tool for Data Breach -- 5.1.2 Facebook-Cambridge Analytical Privacy Breach -- 5.1.3 Consequences of Privacy Failure -- 5.1.4 Research Problem and Objectives -- 5.2 Methodology -- 5.3 Literature Review and Theoretical Development -- 5.3.1 The Concept of Privacy -- 5.3.2 Theoretical Perspectives of Data Breach -- 5.3.3 Social Networking Sites Advertising and Informational Privacy -- 5.3.4 Privacy Concerns and Online Consumers Behaviour -- 5.3.5 Trust and Online Consumer Behaviour -- 5.3.6 Consumers' Online Data Protection -- 5.4 Research Model and Hypotheses -- 5.4.1 Perceived Data Breach -- 5.4.2 Privacy Concerns -- 5.4.3 Trust -- 5.4.4 Emotional Violation -- 5.4.5 Ad Behaviour -- 5.5 Discussion and Implications -- 5.6 Conclusion, Limitations and Scope for Further Research -- References -- 6 Fuzzy DEMATEL Approach to Identify the Factors Influencing Efficiency of Indian Retail Websites -- 6.1 Introduction -- 6.2 Objective -- 6.3 Methodology -- 6.3.1 Fuzzy DEMATEL Approach -- 6.4 Numerical Interpretation -- 6.5 Conclusion -- References -- 7 Application of Statistical Techniques in Project Monitoring and Control -- 7.1 Introduction -- 7.2 Major Challenges in Project Execution and Data Collection [1] -- 7.3 Life Cycle of Metric Data Collection and Analysis -- 7.3.1 Project Data Collection Method -- 7.4 Creation of Process Performance Baseline and Models [2] -- 7.4.1 Process Performance Baseline Creation [3] -- 7.4.2 Process Performance Model Creation -- 7.5 Application of Statistical Techniques in Project Monitoring and Control -- 7.5.1 What-if Analysis [4] -- 7.5.2 Causal Analysis and Resolution (CAR) 7.6 How to Measure Improvements in Projects [5] -- 7.6.1 Two Sample T-Test -- 7.6.2 Two Sample F-Tests -- 7.7 Conclusion -- References -- 8 Sensor-Based Smart Agriculture in India -- 8.1 Introduction -- 8.1.1 Drone Technology -- 8.2 Literature Review -- 8.2.1 Drones in Indian Agriculture -- 8.3 Research Objective -- 8.4 Research Methodology -- 8.5 Findings -- 8.5.1 Drones for Farmers -- 8.5.2 Sensor-Based Technology Used for Agriculture in Some Experiments -- 8.6 Recommendations -- 8.7 Significance of the Study -- References -- 9 Integrating UTAUT with Trust and Perceived Benefits to Explain User Adoption of Mobile Payments -- 9.1 Introduction and Literature Review -- 9.2 Hypothesis and Model Development -- 9.2.1 Unified Theory of Acceptance and Use of Technology (UTAUT) -- 9.2.2 Perceived Benefits (PBN) -- 9.2.3 Trust -- 9.3 Research Methodology -- 9.3.1 Research Design and Research Method -- 9.3.2 Survey Location and Target Respondents -- 9.3.3 Questionnaire Design -- 9.4 Results of the Study -- 9.4.1 Sample Profile -- 9.4.2 Validity and Reliability -- 9.4.3 Model Testing -- 9.5 Discussion and Conclusion -- 9.6 Limitations of the Study and Future Scope -- References -- 10 Improving the Quality of Customer Service of Financial Institutions: The Implementation of Challenger Banks -- 10.1 Introduction -- 10.2 Key Research Findings -- 10.2.1 Ways to Improve the Quality of Customer Service in Financial Institutions -- 10.2.2 Challenger Banks-A New Form of Customer Service -- 10.2.3 Efficiency Evaluation of Challenger Banks -- 10.3 Result of Modeling -- 10.4 Conclusions -- References -- 11 Corporate Image Building in the Indian IT Sector: Conceptualizing Through HR Practices -- 11.1 Introduction -- 11.1.1 Corporate Image -- 11.1.2 Employees and HR Practices -- 11.2 Literature Survey -- 11.2.1 Research Strategy 11.2.2 Corporate Image Building: Conceptual Perspectives -- 11.2.3 HR Practices -- 11.2.4 Employer Branding -- 11.2.5 Corporate Social Responsibility -- 11.2.6 Corporate Social Performance -- 11.3 Methodology -- 11.4 Results and Discussion -- 11.5 Conclusion -- 11.6 Future Scope -- References -- 12 Vague Reliability Analysis of Standby Systems with an (N + 1) Units -- 12.1 Introduction -- 12.2 Notations -- 12.3 Model Description -- 12.4 Mathematical Formulation of the Model -- 12.5 Solution of the Model -- 12.6 Vague Reliability Analysis of the Model -- 12.7 Discussion and Interpretation -- References -- 13 Experimental Study for MRR and TWR on Machining of Inconel 718 using ZNC EDM -- 13.1 Introduction -- 13.2 Literature Survey -- 13.3 Methodology -- 13.4 Results and Discussion -- 13.5 Effect of Factors on MRR and TWR -- 13.6 Conclusions -- 13.7 Future Scope -- References -- 14 Blind Quantitative Steganalysis Using CNN-Long Short-Term Memory Architecture -- 14.1 Introduction -- 14.2 Related Work -- 14.3 Background Concepts -- 14.3.1 Convolutional Neural Networks -- 14.3.2 Long Short-Term Memory Network -- 14.3.3 CNN with LSTM -- 14.3.4 Dense and Dropout Layer -- 14.3.5 Mean Absolute Error -- 14.4 Proposed Framework -- 14.5 Experimental Study -- 14.6 Conclusions -- References -- 15 Performance of Autoregressive Tree Model in Forecasting Cancer Patients -- 15.1 Introduction -- 15.2 Source of Data -- 15.3 Methodology -- 15.4 Result and Discussion -- 15.4.1 Fitted AR Model -- 15.4.2 Fitted ART Model -- 15.4.3 Forecast Trend of Type of Cancer -- 15.4.4 Model Forecasting Comparison -- 15.4.5 Hypothesis Testing -- 15.5 Conclusion -- 15.6 Future Scope -- References -- 16 Developing a Usage Space Dimension Model to Investigate Influence of Intention to Use on Actual Usage of Mobile Phones -- 16.1 Introduction -- 16.2 Literature Review 16.2.1 Mobile Use Practices Among Professionals -- 16.2.2 The UTAUT Model -- 16.2.3 Usage Spaces -- 16.3 Research Gap -- 16.3.1 Purpose of the Study -- 16.4 Research Methodology -- 16.4.1 Data Collection and Survey Procedure -- 16.5 Data Analysis and Results -- 16.5.1 Demographics -- 16.5.2 Individual Mobile Use -- 16.5.3 Reported Usage -- 16.5.4 Reliability Analysis -- 16.5.5 Validity Analysis -- 16.5.6 Confirmatory Factor Analysis -- 16.5.7 Effect of Gender on IE and AU Across the Usage Space Dimensions -- 16.5.8 Effect of Age on IE and AU Across the Usage Space Dimensions -- 16.5.9 Discussions and Conclusions -- 16.6 Limitations, Implications, and Future Research -- Appendix: Reported Usage Across Usage Space Dimensions -- References -- 17 Examining the Relationship Between Customer-Oriented Success Factors, Customer Satisfaction, and Repurchase Intention for Mobile Commerce -- 17.1 Introduction -- 17.2 Related Work and Hypotheses Development -- 17.2.1 M-Commerce Application Success (MAS) -- 17.2.2 Customer Satisfaction (CS) -- 17.2.3 Repurchase Intention (RI) -- 17.3 Methodology -- 17.4 Data Analysis Summary -- 17.4.1 Demographic Profile of the Respondents -- 17.4.2 Validity and Reliability of Measures -- 17.4.3 SEM Results -- 17.5 Discussions and Conclusions -- Appendix -- References -- 18 Smart Industrial Packaging and Sorting System -- 18.1 Introduction -- 18.2 Conventional System -- 18.2.1 Mechanical Arms -- 18.2.2 Hand-Based Sorting System -- 18.2.3 Shape-Based Sorting System -- 18.3 Proposed System Modelling with Flow Chart -- 18.4 Product Specification for Proposed Model -- 18.5 Technical Aspect and Interfacing in the Model -- 18.6 Result -- 18.7 Conclusion -- References -- 19 Credentials Safety and System Security Pay-off and Trade-off: Comfort Level Security Assurance Framework -- 19.1 Introduction -- 19.2 Background 19.3 Right Functionality Management information systems Singh, Ompal Sonstige oth Khatri, Sunil Kumar Sonstige oth Verma, Ajit Kumar Sonstige oth Erscheint auch als Druck-Ausgabe Kapur, P. K. Strategic System Assurance and Business Analytics Singapore : Springer Singapore Pte. Limited,c2020 9789811536465 |
| spellingShingle | Kapur, P. K. Strategic System Assurance and Business Analytics Intro -- Preface -- Acknowledgements -- Contents -- Editors and Contributors -- 1 Investing Data with Machine Learning Using Python -- 1.1 Introduction -- 1.2 Supervised and Unsupervised Machine Learning -- 1.3 Word Done -- 1.3.1 Data Extraction -- 1.3.2 Data Analysis -- 1.3.3 Predictions -- 1.4 Conclusion -- References -- 2 Probabilistic Assessment of Complex System with Two Subsystems in Series Arrangement with Multi-types Failure and Two Types of Repair Using Copula -- 2.1 Introduction -- 2.1.1 State Description -- 2.1.2 Assumptions -- 2.1.3 Notations -- 2.1.4 System Configuration and State Transition Diagram -- 2.2 Mathematical Formulation of the Model -- 2.2.1 Solution of the Model -- 2.3 Analytical Study of the Model for the Particular Case -- 2.4 Result Analysis and Conclusions -- References -- 3 Recognition and Optimizing Process Lagging Indicators During Software Development -- 3.1 Introduction [1] -- 3.2 Major Challenges Faced in Software Development [2] -- 3.3 Equilibrium Between Project Constraints [2, 3] -- 3.3.1 Selection of Triple Constraints [4] -- 3.4 Recognition of Relevant Process Lagging and Leading Indicators [3, 5] -- 3.4.1 Customer Requirement -- 3.4.2 Project Agreement -- 3.4.3 Type of Project -- 3.4.4 Phase of Project -- 3.4.5 Organization Business Goal -- 3.4.6 Recognition of Leading Indicators -- 3.5 Monitoring of Process Lagging and Leading Indicators [3, 6] -- 3.6 Optimization of Process Lagging and Leading Indicators [6] -- 3.7 Conclusion -- References -- 4 Risk and Safety Analysis of Warships Operational Lifetime Defects -- 4.1 Introduction -- 4.2 Warship Design Cycle -- 4.2.1 Warship Design Production and Operation Lifecycle -- 4.2.2 Warship Design Production and Operation Lifecycle-Risks and Mitigation Regime -- 4.2.3 Warship-Systems Approach -- 4.3 Case Study -- 4.3.1 Methodology of Study 4.3.2 Risk Calculation -- 4.3.3 The Analysis -- 4.4 The Conclusion -- 4.5 Way Ahead -- References -- 5 Facebook Data Breach: A Systematic Review of Its Consequences on Consumers' Behaviour Towards Advertising -- 5.1 Introduction -- 5.1.1 Applications as a Tool for Data Breach -- 5.1.2 Facebook-Cambridge Analytical Privacy Breach -- 5.1.3 Consequences of Privacy Failure -- 5.1.4 Research Problem and Objectives -- 5.2 Methodology -- 5.3 Literature Review and Theoretical Development -- 5.3.1 The Concept of Privacy -- 5.3.2 Theoretical Perspectives of Data Breach -- 5.3.3 Social Networking Sites Advertising and Informational Privacy -- 5.3.4 Privacy Concerns and Online Consumers Behaviour -- 5.3.5 Trust and Online Consumer Behaviour -- 5.3.6 Consumers' Online Data Protection -- 5.4 Research Model and Hypotheses -- 5.4.1 Perceived Data Breach -- 5.4.2 Privacy Concerns -- 5.4.3 Trust -- 5.4.4 Emotional Violation -- 5.4.5 Ad Behaviour -- 5.5 Discussion and Implications -- 5.6 Conclusion, Limitations and Scope for Further Research -- References -- 6 Fuzzy DEMATEL Approach to Identify the Factors Influencing Efficiency of Indian Retail Websites -- 6.1 Introduction -- 6.2 Objective -- 6.3 Methodology -- 6.3.1 Fuzzy DEMATEL Approach -- 6.4 Numerical Interpretation -- 6.5 Conclusion -- References -- 7 Application of Statistical Techniques in Project Monitoring and Control -- 7.1 Introduction -- 7.2 Major Challenges in Project Execution and Data Collection [1] -- 7.3 Life Cycle of Metric Data Collection and Analysis -- 7.3.1 Project Data Collection Method -- 7.4 Creation of Process Performance Baseline and Models [2] -- 7.4.1 Process Performance Baseline Creation [3] -- 7.4.2 Process Performance Model Creation -- 7.5 Application of Statistical Techniques in Project Monitoring and Control -- 7.5.1 What-if Analysis [4] -- 7.5.2 Causal Analysis and Resolution (CAR) 7.6 How to Measure Improvements in Projects [5] -- 7.6.1 Two Sample T-Test -- 7.6.2 Two Sample F-Tests -- 7.7 Conclusion -- References -- 8 Sensor-Based Smart Agriculture in India -- 8.1 Introduction -- 8.1.1 Drone Technology -- 8.2 Literature Review -- 8.2.1 Drones in Indian Agriculture -- 8.3 Research Objective -- 8.4 Research Methodology -- 8.5 Findings -- 8.5.1 Drones for Farmers -- 8.5.2 Sensor-Based Technology Used for Agriculture in Some Experiments -- 8.6 Recommendations -- 8.7 Significance of the Study -- References -- 9 Integrating UTAUT with Trust and Perceived Benefits to Explain User Adoption of Mobile Payments -- 9.1 Introduction and Literature Review -- 9.2 Hypothesis and Model Development -- 9.2.1 Unified Theory of Acceptance and Use of Technology (UTAUT) -- 9.2.2 Perceived Benefits (PBN) -- 9.2.3 Trust -- 9.3 Research Methodology -- 9.3.1 Research Design and Research Method -- 9.3.2 Survey Location and Target Respondents -- 9.3.3 Questionnaire Design -- 9.4 Results of the Study -- 9.4.1 Sample Profile -- 9.4.2 Validity and Reliability -- 9.4.3 Model Testing -- 9.5 Discussion and Conclusion -- 9.6 Limitations of the Study and Future Scope -- References -- 10 Improving the Quality of Customer Service of Financial Institutions: The Implementation of Challenger Banks -- 10.1 Introduction -- 10.2 Key Research Findings -- 10.2.1 Ways to Improve the Quality of Customer Service in Financial Institutions -- 10.2.2 Challenger Banks-A New Form of Customer Service -- 10.2.3 Efficiency Evaluation of Challenger Banks -- 10.3 Result of Modeling -- 10.4 Conclusions -- References -- 11 Corporate Image Building in the Indian IT Sector: Conceptualizing Through HR Practices -- 11.1 Introduction -- 11.1.1 Corporate Image -- 11.1.2 Employees and HR Practices -- 11.2 Literature Survey -- 11.2.1 Research Strategy 11.2.2 Corporate Image Building: Conceptual Perspectives -- 11.2.3 HR Practices -- 11.2.4 Employer Branding -- 11.2.5 Corporate Social Responsibility -- 11.2.6 Corporate Social Performance -- 11.3 Methodology -- 11.4 Results and Discussion -- 11.5 Conclusion -- 11.6 Future Scope -- References -- 12 Vague Reliability Analysis of Standby Systems with an (N + 1) Units -- 12.1 Introduction -- 12.2 Notations -- 12.3 Model Description -- 12.4 Mathematical Formulation of the Model -- 12.5 Solution of the Model -- 12.6 Vague Reliability Analysis of the Model -- 12.7 Discussion and Interpretation -- References -- 13 Experimental Study for MRR and TWR on Machining of Inconel 718 using ZNC EDM -- 13.1 Introduction -- 13.2 Literature Survey -- 13.3 Methodology -- 13.4 Results and Discussion -- 13.5 Effect of Factors on MRR and TWR -- 13.6 Conclusions -- 13.7 Future Scope -- References -- 14 Blind Quantitative Steganalysis Using CNN-Long Short-Term Memory Architecture -- 14.1 Introduction -- 14.2 Related Work -- 14.3 Background Concepts -- 14.3.1 Convolutional Neural Networks -- 14.3.2 Long Short-Term Memory Network -- 14.3.3 CNN with LSTM -- 14.3.4 Dense and Dropout Layer -- 14.3.5 Mean Absolute Error -- 14.4 Proposed Framework -- 14.5 Experimental Study -- 14.6 Conclusions -- References -- 15 Performance of Autoregressive Tree Model in Forecasting Cancer Patients -- 15.1 Introduction -- 15.2 Source of Data -- 15.3 Methodology -- 15.4 Result and Discussion -- 15.4.1 Fitted AR Model -- 15.4.2 Fitted ART Model -- 15.4.3 Forecast Trend of Type of Cancer -- 15.4.4 Model Forecasting Comparison -- 15.4.5 Hypothesis Testing -- 15.5 Conclusion -- 15.6 Future Scope -- References -- 16 Developing a Usage Space Dimension Model to Investigate Influence of Intention to Use on Actual Usage of Mobile Phones -- 16.1 Introduction -- 16.2 Literature Review 16.2.1 Mobile Use Practices Among Professionals -- 16.2.2 The UTAUT Model -- 16.2.3 Usage Spaces -- 16.3 Research Gap -- 16.3.1 Purpose of the Study -- 16.4 Research Methodology -- 16.4.1 Data Collection and Survey Procedure -- 16.5 Data Analysis and Results -- 16.5.1 Demographics -- 16.5.2 Individual Mobile Use -- 16.5.3 Reported Usage -- 16.5.4 Reliability Analysis -- 16.5.5 Validity Analysis -- 16.5.6 Confirmatory Factor Analysis -- 16.5.7 Effect of Gender on IE and AU Across the Usage Space Dimensions -- 16.5.8 Effect of Age on IE and AU Across the Usage Space Dimensions -- 16.5.9 Discussions and Conclusions -- 16.6 Limitations, Implications, and Future Research -- Appendix: Reported Usage Across Usage Space Dimensions -- References -- 17 Examining the Relationship Between Customer-Oriented Success Factors, Customer Satisfaction, and Repurchase Intention for Mobile Commerce -- 17.1 Introduction -- 17.2 Related Work and Hypotheses Development -- 17.2.1 M-Commerce Application Success (MAS) -- 17.2.2 Customer Satisfaction (CS) -- 17.2.3 Repurchase Intention (RI) -- 17.3 Methodology -- 17.4 Data Analysis Summary -- 17.4.1 Demographic Profile of the Respondents -- 17.4.2 Validity and Reliability of Measures -- 17.4.3 SEM Results -- 17.5 Discussions and Conclusions -- Appendix -- References -- 18 Smart Industrial Packaging and Sorting System -- 18.1 Introduction -- 18.2 Conventional System -- 18.2.1 Mechanical Arms -- 18.2.2 Hand-Based Sorting System -- 18.2.3 Shape-Based Sorting System -- 18.3 Proposed System Modelling with Flow Chart -- 18.4 Product Specification for Proposed Model -- 18.5 Technical Aspect and Interfacing in the Model -- 18.6 Result -- 18.7 Conclusion -- References -- 19 Credentials Safety and System Security Pay-off and Trade-off: Comfort Level Security Assurance Framework -- 19.1 Introduction -- 19.2 Background 19.3 Right Functionality Management information systems |
| title | Strategic System Assurance and Business Analytics |
| title_auth | Strategic System Assurance and Business Analytics |
| title_exact_search | Strategic System Assurance and Business Analytics |
| title_full | Strategic System Assurance and Business Analytics |
| title_fullStr | Strategic System Assurance and Business Analytics |
| title_full_unstemmed | Strategic System Assurance and Business Analytics |
| title_short | Strategic System Assurance and Business Analytics |
| title_sort | strategic system assurance and business analytics |
| topic | Management information systems |
| topic_facet | Management information systems |
| work_keys_str_mv | AT kapurpk strategicsystemassuranceandbusinessanalytics AT singhompal strategicsystemassuranceandbusinessanalytics AT khatrisunilkumar strategicsystemassuranceandbusinessanalytics AT vermaajitkumar strategicsystemassuranceandbusinessanalytics |