داده‌های کلان در هنرها و علوم انسانی: نظریه و عمل (کاربردهای تحلیل داده)

As digital technologies occupy a more central role in working and everyday human life, individual and social realities are increasingly constructed and communicated through digital objects, which are progressively replacing and representing physical objects. They are even shaping new forms of virtual reality. This growing digital transformation coupled with technological evolution and the development of computer computation is shaping a cyber society whose working mechanisms are grounded upon the production, deployment, and exploitation of big data. In the arts and humanities, however, the notion of big data is still in its embryonic stage, and only in the last few years, have arts and cultural organizations and institutions, artists, and humanists started to investigate, explore, and experiment with the deployment and exploitation of big data as well as understand the possible forms of collaborations based on it. Big Data in the Arts and Humanities: Theory and Practice explores the meaning, properties, and applications of big data. This book examines therelevance of big data to the arts and humanities, digital humanities, and management of big data with and for the arts and humanities. It explores the reasons and opportunities for the arts and humanities to embrace the big data revolution. The book also delineates managerial implications to successfully shape a mutually beneficial partnership between the arts and humanities and the big data- and computational digital-based sciences. Big data and arts and humanities can be likened to the rational and emotional aspects of the human mind. This book attempts to integrate these two aspects of human thought to advance decision-making and to enhance the expression of the best of human life. This book offers a look at the current state of Big Data, including a comprehensive overview of both research and practical applications. Cover 1 Half Title 2 Series Page 3 Title Page 4 Copyright Page 5 Dedication 6 Table of Contents 8 Foreword 10 Foreword 12 Preface 14 Editor 18 Contributors 20 Section I: Big Data and Management: Theoretical Foundations 28 1 Big Data Analytics: Innovation Management and Value Creation 30 1.1 Introduction 30 1.2 Research Method 31 1.3 Big Data Analytics: The Innovation Driver 32 1.4 Value Creation through Innovation 34 1.4.1 Creating Value for an Organization Using Information Resources and ICT 34 1.4.2 Creating Value for the Consumer through Innovation 35 1.4.3 Value Creation through Innovation: Conceptual Model 36 1.5 Conclusions 37 References 38 2 Human Resource Management in the Era of Big Data 44 2.1 Introduction 44 2.2 Influence of Big Data on HRM 45 2.3 HRM and Big Data As a Subject of Interests 48 2.4 Results of the Analysis 51 2.5 Conclusions and Future Research 59 References 59 3 Knowledge Management and Big Data in Business 64 3.1 Introduction 64 3.2 Situation and Challenges in Theory and Practice of Knowledge Management in the Era of the Big Data 65 3.3 Evidence-Based Management versus Knowledge Management in the Big Data Era 68 3.4 Improvement of Business Processes Using the Management Concept Based on Big Data 69 3.5 Improving Student Onboarding Using the Knowledge Management Conception Based on Big Data Analysis and Gamification 72 3.5.1 Situation Analysis 72 3.5.2 Shortcomings of the Current Onboarding System 73 3.5.3 The Conception of Student Onboarding Improvement Using Big Data Acquired in the Serious Game 74 3.6 Conclusion 76 References 76 4 Information Management and the Role of Information Technology in a Big Data Era 80 4.1 Introduction 81 4.2 The Big Data Perspective 81 4.3 Literature Review and Synthesis 82 4.4 Information Management in the Big Data Perspective 83 4.4.1 Information System and Managerial Information System 83 4.4.2 Decision-Making Processes and Decision-Makers 89 4.4.3 Organization Culture 89 4.5 Role of Information Technologies in the Era of Big Data 90 4.5.1 Date Warehouses 90 4.5.2 Distributed and Parallel Processing of Big Data Sets 91 4.5.3 Machine Learning 92 4.6 Conclusions 93 References 94 5 Financial Management in the Big Data Era 98 5.1 Introduction 99 5.2 Big Data Characteristics in Financial Management 99 5.3 Implementation of Big Data Technologies for Supporting Financial Management Decision 100 5.3.1 Financial and Non-Financial Organizations 100 5.3.1.1 Financial Institutions 100 5.3.1.2 Non-Financial Companies 101 5.3.2 Capital Market Investments 102 5.3.3 Risk Management 103 5.3.4 Financial Markets 104 5.3.5 Accounting Data Processing 104 5.3.6 Budget Management 104 5.3.7 Controlling and Audits 105 5.4 Conclusions 105 References 106 6 Ethics and Trust to Big Data in Management: Balancing Risk and Innovation 110 6.1 Introduction 111 6.2 The Digital Risk Associated with Big Data 111 6.3 Trust in Big Data 112 6.4 Building a Sensible Trust in Big Data in Organization Management 114 6.5 The Impact of Data Ethics Solutions on Organizational Innovation and Organization Management in the Digital Age 115 6.6 Balancing Digital Security with the Innovation Risk in Evidence-Based Management Using Big Data 117 6.7 Conclusion 118 References 119 Section II: Big Data in Management: Applications,Prospects, and Challenges 122 7 Big Data in Modern Farm Management 124 7.1 Introduction 124 7.2 Farm Management before the Era of Big Data 126 7.3 Big Data in Animal Production Management 128 7.4 Advantages of Big Data in Farm Management 128 7.5 Disadvantages of Big Data in Farm Management 132 7.6 Farmers’ Perception of Big Data 134 7.7 Conclusions and Proposition for Future Research 135 References 136 8 Big Data Analytics and Corporate Social Responsibility: An Example of the Agribusiness Sector 142 8.1 Introduction 142 8.2 Premises for Changes in the Agribusiness Sector 143 8.3 Methodology 145 8.4 Research Results 146 8.5 Conclusion 150 References 151 9 Big Data Analytics in Tourism: Overview and Trends 154 9.1 Introduction 154 9.2 Conditions for Using Big Data Analysis in the Tourism Industry 155 9.3 The Use of Big Data in Tourism 158 9.4 Trends in the Use of Big Data in Tourism 159 9.5 Conclusion 160 References 161 10 Use of Big Data for Assessment of Environmental Pressures from Agricultural Production 164 10.1 Introduction 165 10.1.1 Farm Accountancy Data Network (FADN) 166 10.1.2 GHG Emissions: Challenge for the Farming Sector 167 10.2 Methodology 168 10.3 Results 170 10.4 Discussion and Conclusions 175 References 176 11 Big Data as a Key Aspect of Customer Relationship Management: An Example of the Restaurant Industry 180 11.1 Introduction 181 11.2 Customer Relationship Management 182 11.3 Analysis of the Gastronomy Market in Poland 182 11.4 Structure of Consumer Spending 183 11.5 Characteristics of the Pizzeria “L’Olivo” 184 11.6 Digitization and Use of Data on Consumer Behavior in Creating a Personalized Offer 187 11.7 Research on Consumer Behavior in Creating Strategies for Influencing Purchasing Decisions 188 11.8 Conclusion 189 References 190 12 Blockchain and Big Data: Example of Management of Beef Production 192 12.1 Introduction 192 12.2 Statement of the Problem 193 12.3 The Genesis of Blockchain Technology and Its Development Stages 194 12.4 The Concept of Using Blockchain Technology and Factors Limiting It in Beef Production in Poland 197 12.5 Conclusions, Limitations, and Further Research 200 References 201 13 Big Data Analysis for Management from Solow’s Paradox Perspective in Polish Industry 204 13.1 Introduction 204 13.2 Big Data 206 13.3 Scope, Data Sources, and Methods 210 13.4 Results 211 13.5 Conclusion 217 References 218 14 Big Data on Commuting: Application for Business 220 14.1 Introduction 220 14.2 Review of the Literature 222 14.3 Methodology 222 14.4 Results 223 14.5 Discussion 223 14.6 Conclusion 225 References 226 15 How to Support Real-Time Quantitative Big Data by More Future-Orientated Qualitative Data for Understanding Everyday Innovative Businesses? 228 15.1 Introduction 229 15.2 The Oretical Background 230 15.2.1 Innovation 230 15.3 Research Gap 231 15.4 Method 232 15.4.1 Analytical Hierarchy Process 232 15.4.2 Innovation Strategy Index 232 15.4.3 Weak Market Test 234 15.5 Empirical Research 235 15.6 Sample and Analysis 235 15.6.1 Case Company 1 235 15.6.2 Case Company 2 237 15.7 Discussion 239 15.8 Conclusion 240 References 240 Index 244 Big,Data;,Human,Resource,Management;,Modern,Farm,Management;,Blockchain;,Beef,Production;,Real-Time,Quantitative Big Data,Human Resource Management,Modern Farm Management,Blockchain,Beef Production,Real-Time Quantitative As digital technologies occupy a more central role in working and everyday human life, individual and social realities are increasingly constructed and communicated through digital objects, which are progressively replacing and representing physical objects. They are even shaping new forms of virtual reality. This growing digital transformation coupled with technological evolution and the development of computer computation is shaping a cyber society whose working mechanisms are grounded upon the production, deployment, and exploitation of big data. In the arts and humanities, however, the notion of big data is still in its embryonic stage, and only in the last few years, have arts and cultural organizations and institutions, artists, and humanists started to investigate, explore, and experiment with the deployment and exploitation of big data as well as understand the possible forms of collaborations based on it. Big Data in the Arts and Humanities: Theory and Practice explores the meaning, properties, and applications of big data. This book examines therelevance of big data to the arts and humanities, digital humanities, and management of big data with and for the arts and humanities. It explores the reasons and opportunities for the arts and humanities to embrace the big data revolution. The book also delineates managerial implications to successfully shape a mutually beneficial partnership between the arts and humanities and the big data- and computational digital-based sciences. Big data and arts and humanities can be likened to the rational and emotional aspects of the human mind. This book attempts to integrate these two aspects of human thought to advance decision-making and to enhance the expression of the best of human life.-- Provided by Publisher This books sheds light on the unique and creative contributions that the arts and humanities can make to the development of approaches to use big data effectively. It also explores opportunities and challenges for research in the arts and humanities created by the development in the capability to handle, exploit, and use huge and complex datasets in more and more sophisticated ways. The book gives a clear understanding of the potential of big data in driving a step-change in the way the creative and cultural fields fruitfully engage with data to generate significant benefits and value This books sheds light on the unique and creative contributions that the arts and humanities can make to the development of approaches to effectively use big data. It also looks at opportunities and challenges for research in the arts and humanities created by the capability to handle and use sophisticatedly very huge and complex data sets.