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| 020 | | | \a 9783319727455 \q electronic bk. |
| 020 | | | \a 3319727451 \q electronic bk. |
| 024 | 7 | | \a 10.1007/978-3-319-72745-5 \2 doi |
| 050 | | 4 | \a HD30.215 |
| 245 | 0 | 0 | \a Recent developments in data science and business analytics : \b proceedings of the International Conference on Data Science and Business Analytics (ICDSBA- 2017) / \c Madjid Tavana, Srikanta Patnaik, editors. |
| 264 | | 1 | \a Cham, Switzerland : \b Springer, \c 2018. |
| 264 | | 4 | \c © 2018. |
| 300 | | | \a 1 online resource (xvi,505 pages) : \b illustrations. |
| 336 | | | \a text \b txt \2 rdacontent |
| 337 | | | \a computer \b c \2 rdamedia |
| 338 | | | \a online resource \b cr \2 rdacarrier |
| 347 | | | \a text file \b PDF \2 rda |
| 490 | 1 | | \a Springer proceedings in business and economics |
| 504 | | | \a Includes bibliographical references and index. |
| 505 | 0 | | \6 880-01 \a Intro; Preface; Acknowledgments; Contents; About the Editors; Part I: Marketing and Supply Chain Analytics; Chapter 1: Research on Differential Pricing and Coordination Mechanism of Second-Class Supply Chain of New Products and Remanu ... ; 1.1 Literature; 1.2 Problem Description and Modeling; 1.2.1 Problem Description and Assumptions; 1.2.2 Parameters of the Model; 1.2.3 Model Establishment; 1.2.3.1 Decentralized Decision; 1.2.3.2 Equation Solving; 1.2.3.3 Centralized Decision; 1.3 Supply Chain Coordination; 1.3.1 Shapley Value Method; 1.3.2 Part Alliance; 1.4 Numerical Analysis. |
| 505 | 8 | | \a 2.4 ConclusionReferences; Chapter 3: The Quality Management of Food Supply Chain in Perspective of Food Safety; 3.1 Introduction; 3.2 Literature Review; 3.3 SCQM Models for Food Safety; 3.3.1 Supplier Selection; 3.3.2 Supplier Participation; 3.3.3 Quality Management Practice; 3.4 Case Study of Yili; 3.4.1 Suppliers Management; 3.4.2 International Quality Control Standard; 3.4.3 Process Quality Control System; 3.5 Discussion and Conclusions; References; Chapter 4: Strategic Customer Behavior with Risk Preference for a Supply Chain Management Based on Double Channel; 4.1 Introduction. |
| 505 | 8 | | \a 4.2 Literature Review4.3 Model of Strategic Customer; 4.3.1 Model Setup and Rational Expectations Equilibrium; 4.3.2 Retailers and Manufacturers Strategies; 4.4 Model of Strategic Customer with Risk Preference; References; Chapter 5: Competition and Coordination in Single-Supplier Multiple-Retailer Supply Chain; 5.1 Introduction; 5.2 Literature Review; 5.3 Model; 5.3.1 Basic Setup; 5.3.2 Equilibrium in Centralized Case; 5.3.3 Equilibrium in the Decentralized Case; 5.3.4 Coordination with Two-Part Tariff Mechanism; 5.4 Numerical Example; 5.5 Conclusions; References. |
| 505 | 8 | | \a Chapter 6: Research on the Construction of Enterprise Brand Competitiveness Evaluation System Based on the Integration of SWOT ... 6.1 Introduction; 6.2 Literature Review; 6.3 Enterprise Brand Competitiveness Evaluation System; 6.4 Evaluation of Enterprise Brand Competitiveness; 6.4.1 Determine Indexes Weight by AHP; 6.4.2 The Index Weight of the Enterprise Brand Competitiveness Evaluation System; 6.5 Conclusion and Discussion; References; Chapter 7: Reflections on the Training Mode of E-Commerce Professionals with Improved Practical Exercises and Innovative Abili ... ; 7.1 Introduction. |
| 520 | | | \a This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains. |
| 650 | | 0 | \a Management \x Statistical methods \x Data processing. |
| 650 | | 0 | \a Decision making \x Statistical methods \x Data processing. |
| 655 | | 0 | \a Electronic books \2 lcgft |
| 700 | 1 | | \a Tavana, Madjid, \d 1957- \e editor. |
| 700 | 1 | | \a Patnaik, Srikanta, \e editor. |
| 711 | 2 | | \a International Conference on Data Science and Business Analytics \d (2017 : \c Changsha, Hunan Sheng, China) |
| 830 | | 0 | \a Springer proceedings in business and economics. |
| 880 | 8 | | \6 505-01/(S \a 1.5 ConclusionsReferences; Chapter 2: A Study on Cooperation Strategies of Dual Channel Supply Chain Based on Service Level; 2.1 Introduction; 2.2 Model Description and Optimal Decision Making; 2.2.1 Model Hypothesis; 2.2.2 Optimal Decision Under Decentralized Decision; 2.2.3 Optimal Decision Under Centralized Decision Making; 2.3 Model Conclusion and Numerical Analysis; 2.3.1 Model Results Analysis; 2.3.2 Numerical Analysis; 2.3.2.1 When the Acceptance of Network Direct Marketing Channel Is Higher ((So (B= 0.8); 2.3.2.2 When the Acceptance of Network Direct Marketing Channel Is Lower ((So (B= 0.2). |
| 938 | | | \a EBSCOhost \b EBSC \n 1743510 |