Advanced
search

Prelims

Internet+ and Electronic Business in China: Innovation and Applications

ISBN: 978-1-78743-116-4, eISBN: 978-1-78743-115-7

Publication date: 13 December 2017

pdf (4.6 MB) ePub (2.3 MB) Article view Figure view Cited (18) cite article

Abstract

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

Citation

(2017), "Prelims", Ye, Q. and Ma, B. (Ed.) Internet+ and Electronic Business in China: Innovation and Applications, Emerald Publishing Limited, Leeds, pp. i-xx. https://doi.org/10.1108/978-1-78743-115-720171022

Publisher

:

Emerald Publishing Limited

Copyright © 2018 Emerald Publishing Limited

Half Title Page

Internet+ and Electronic Business in China

Innovation and Applications

Title Page

Internet+ and Electronic Business in China

Innovation and Applications

Edited By

Qiongwei Ye

Yunnan University of Finance and Economics, China

Baojun Ma

Beijing University of Posts and Telecommunications, China

United Kingdom – North America – Japan India – Malaysia – China

Copyright Page

Emerald Publishing Limited

Howard House, Wagon Lane, Bingley BD16 1WA, UK

First edition 2018

Copyright © 2018 Emerald Publishing Limited

Reprints and permissions service

Contact: permissions@emeraldinsight.com

No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters' suitability and application and disclaims any warranties, express or implied, to their use.

British Library Cataloguing in Publication Data

A catalogue record for this book is available from the British Library

ISBN: 978-1-78743-116-4 (Print)

ISBN: 978-1-78743-115-7 (Online)

ISBN: 978-1-78743-176-8 (Epub)

Contents

Foreword xviii
Part I Theoretical Foundation of E-Commerce 1
Chapter 1 Connotation of E-Commerce 3
 1. Definition of E-commerce 3
 2. Emerging Characteristics of E-business 6
 3. E-business and Personalization 8
 4. Notes 11
 5. References 11
CHAPTER 2 E-BUSINESS MODELS 13
 1. Basic E-business Models 13
 2. E-business Model Innovations 22
 3. References 26
Chapter 3 E-Business Intelligence 27
 1. Definition of Business Intelligence 27
 2. Multi-dimensional Analysis of Business Intelligence Application in E-business Enterprises 28
 3. An Information Value Analysis of Business Intelligence Application 29
 4. A Technical Analysis of Business Intelligence Application 31
 5. Analysis of the Application Phases of Business Intelligence 32
 6. Application of Business Intelligence in E-business Enterprises 34
 7. Business Intelligence and Virtual Value Chain (VVC) 34
 8. Application of Business Intelligence in Customer Relationship Management as Based on Virtual Value Chain 37
 9. Application of Business Intelligence in Supply Chain Management 40
 10. References 55
Chapter 4 E-Business Logistics 57
 1. Information Network of Things and Modern Logistics 57
 2. The Supply and Marketing Cooperative – The Modern Logistics Network in the Country 87
 3. Internet of Things (IOT) and E-business 94
 4. Notes 97
 5. References 97
Part Ii Internet + E-Business Model Innovations 99
Chapter 5 Internet + Agriculture 101
 1. Introduction 101
 2. General Introduction to the Theory 102
 3. Case Study of Mitubaba’s Social E-commerce Model of Special Plateau Agricultural Products 119
 4. Case Study of a Walnut Oil Business’s B2S2C Model 128
 5. Case Study of Chu’s Orange’s Social Business Marketing of Agricultural Products 142
 6. Case Study of TDJ’s Full Value Chain Special Product Mall 148
 7. Case Study of NYW’s Agricultural E-business Platform 155
 8. Summary 171
 9. Notes 172
 10. References 172
Chapter 6 Social Business 175
 1. Introduction 175
 2. Social Networks 176
 3. Case Study of a Virtual Community E-business on Social Networks 202
 4. Notes 221
 5. References 221
Chapter 7 O2O 223
 1. Introduction 223
 2. Relevant O2O Model Theories 223
 3. Case Study of Meituan–Dianping 228
 4. Conclusions 237
 5. Questions for Further Thought 237
 6. Notes 237
 7. References 238
Chapter 8 Internet Financing 239
 1. Introduction 239
Section 1 Internet Finance Theory 240
 1. Brief Introduction to Internet Financing 240
 2. Types of Internet Finance 242
 3. Internet Finance Features 245
 4. Relevant Studies of Internet Finance 247
 5. Current Development Status of Internet Financing 248
 6. Conclusions 256
Section 2 Case Studies of “Finance+Internet” 257
 1. Theoretical Foundation of “Finance+Internet” 257
 2. A Case Study of Lufax’s “Finance+Internet” 260
 3. A Case Study of Oriental Exchange’s “Finance+Internet” 265
 4. Summary of “Finance+Internet” 270
Section 3 Case Studies of “Internet+Finance” 271
 1. Theoretical Foundation of “Internet+Finance” 271
 2. A Case Study of YuEBao’s “Internet+Finance” 273
 3. A Case Study of Jingdong’s Supply Chain “Internet+Finance” 277
 4. Conclusions 283
 5. Notes 283
 6. References 284
Part III E-Business Platform Applications 287
Chapter 9 Bilateral Market 289
 1. Introduction 289
Section 1 Competitive Behavior of E-business Platform Enterprises 290
 1. Related Theory 290
 2. Analysis of the Competitive Behavior of Dangdang.com and Amazon.CN 301
 3. Comments on the Case 308
 4. Questions for Further Thought 310
 5. Conclusions 310
Section 2 Pricing Strategy of Social Network Platforms 312
 1. Introduction to the Theory 313
 2. Case Study of Renren.com 319
 3. Comments on the Case 334
 4. Questions for Further Thought 335
 5. Conclusions 335
 6. Notes 336
 7. References 336
Chapter 10 E-Business Platform Information Search Services 339
 1. Introduction 339
 2. Information Retrieval Model Review 343
 3. Review of Evaluation Measure Related to Information Search Services 349
 4. Overview of Relevant Extraction Methods in Information Search Services 357
 5. Conclusions 361
 6. Notes 363
 7. References 363
Chapter 11 Diversity Assessment of E-Business Platform Information Search Services 369
 1. Introduction 369
 2. Information Coverage Measure 374
 3. Measure of Information Redundancy 385
 4. Measure Calculation Processes and Examples for Measure Comparison 388
 5. Actual Application Scenarios and Case Studies 395
 6. Notes 400
 7. References 400
Chapter 12 Extraction Algorithms of Diverse E-Business Platform Information Search Services 403
 1. Introduction 403
 2. The Heuristic Algorithm Based on Information Coverage 406
 3. The Heuristic Algorithm Based on Information Coverage and Information Redundancy 422
 4. A Comparative Study of Diversity Extraction Measurements 424
 5. References 426
Chapter 13 Emotional Analysis of Online Reviews on E-Business Platforms 429
 1. Introduction 429
 2. Emotional Clustering Setting in Online Reviews 431
 3. Result Analysis of the Emotional Clustering Experiments 440
 4. Future Development of Emotional Clustering in Online Reviews 451
 5. Actual Application Scenarios and Case Studies 454
 6. References 456
Chapter 14 Semantic Search of Online Reviews on E-Business Platforms 461
 1. Introduction 461
 2. Semantic Search Framework Based on Probabilistic Topic Modeling 466
 3. Probabilistic Topic Modeling Phases 470
 4. User’s Semantic Search Phases 474
 5. Actual Application Scenarios and Case Studies 475
 6. References 478
Part IV Practice Of Internet + E-Business Projects 483
Chapter 15 Internet + Resource Enterprises 485
 1. Introduction 485
 2. A General Introduction to the Theory 486
 3. Project: The DY Coal Group 490
 4. Comments on the Project 503
 5. Questions for Further Thought 504
 6. Conclusions 504
 7. References 505
Chapter 16 Mobile Internet 507
 1. Introduction 507
 2. A General Introduction to the Theory 507
 3. Project: Yunnan Mobile 515
 4. Comments on the Project 531
 5. Questions for Further Thought 532
 6. Conclusions 532
 7. References 533
Chapter 17 The Business Intelligence System Based on Big Data 535
 1. Introduction 535
 2. Relevant Theories 536
 3. Project: Implementation of Ke Chuan’s Business Intelligence System 545
 4. Comments on the Project 552
 5. Questions for Further Thought 554
 6. Conclusions 554
 7. Note 555
 8. References 555
Chapter 18 The Social Campus Witkey System 557
 1. Introduction 557
 2. A General Introduction to the Theory 558
 3. Project: The Social Campus Witkey System 562
 4. Comments on the Project 570
 5. Questions for Further Thought 571
 6. Conclusions 572
 7. Notes 572
 8. References 572
About the authors 575
Index 577

List of tables and figures

Figures

1.1. Broad Definition of E-business. 5
3.1. The Time Dimension Model of Business Intelligence Application. 29
3.2. The Information Value Dimension Model of Business Intelligence. 30
3.3. The Technical Dimension Model of Business Intelligence. 31
3.4. Shopping Center’s Business Distribution Chart by Type. 39
3.5. The Shopping Center’s Flow Chart for Recruiting Businesses. 42
3.6. Procurement and Administration Process. 49
3.7. Procurement and Return Process. 50
3.8. Application of BI at the Retail Stores of YNYY Pharmaceutical Chain. 51
3.9. Intelligent Management of Inventory Replenishment for Retail Stores. 52
4.1. RFID Tag Internal Structure (Chip and Antenna). 74
4.2. RFID System Composition. 74
4.3. Logistics System Based on RFID Technology. 78
4.4. System Structure of Logistics Information Network. 84
4.5. Agricultural E-commerce Site System’s Front Page. 86
4.6. Agricultural E-commerce Site System’s Back Page. 86
4.7. Modern Rural Commodity Circulation Network Model of Supply and Marketing Cooperatives. 92
4.8. An Agricultural Products Supermarket Marketing Automation to Achieve the User Interface. 94
4.9. An Agricultural Product Supermarket Promotion Automation Interface. 95
5.1. B2S2C Model Structure. 109
5.2. Mitubaba Mobile (WeChat) Homepage. 110
5.3. Mitubaba Homepage on PC Terminals. 120
5.4. Operation Process Chart of Mitubaba Agricultural Product Shopping Platform. 123
5.5. Mitu E-life Structure Chart. 124
5.6. Cross-platform Integration Model Diagram. 125
5.7. User Conversion Diagram. 126
5.8. Financial Status of XS Company. 136
5.9. Value Flow Diagram of TDJ Mall. 150
5.10. Transaction Flow Diagram. 152
5.11. Website Homepage of Agricultural E-business. 157
6.1. The Strength of Interpersonal Relationship Linkage of Facebook (Left) and the United States. 179
6.2. The Comparison Diagrams of the Degree of Spread between Cluster Network and Random Network. 181
6.3. Framework of Facebook’s Technology Model. 196
6.4. The Structure Graph of Social Network. 206
6.5. Changes in Profits Before and After Water Margin’s Business Model Adjustments. 209
6.6. Technological Framework of WeChat. 214
6.7. Ecological Ripple Effect of WeChat. 220
8.1. Lufax’s Internet Finance Platform. 261 8.2. The Comprehensive Internet Financial Platform of Eastlending. 266 9.1. Two-sided Market Structure. 291
9.2. Competition among Platforms. 292
9.3. Publication Market Share Proportion of Dangdang.com (P1) and Chinese Publication Market Share Proportion of Amazon.cn (P2). 305
9.4. The Increase of Randomness Leads to the Change of Network Topology 314
9.5. Betrayer Intrudes Cooperator Under the Game of Prisoner’s Dilemma. 315
9.6. Path Analysis of Marketing Values of Social Network 318
9.7. Changes in Consumer Quantity and Advertising Income. 327
9.8. Number of Social Users and Online Advertising Prices of Renren after Removal of Seasonal Factors. 327
9.9. Monthly Independent Users and Online Advertising Revenue of Renren in Q1 2010–Q1 2015. 330
9.10. Comparison of Actual Value and Predicted Value of Online Advertising Revenue of Renren by the Cumulative Triple Exponential Smoothing Algorithm (α = 0.55, β = 0.25, γ = 0.45, and the Number of Periodic Observations Is 2). 330
9.11. Data Prediction Results After the Comparison of the Linear Regression Analysis and Triple Exponential Smoothing Algorithm. 331
9.12. Fitting Results after Adjustment. 333
11.1. Example 1. 371
11.2. Illustration of Extended Examples of Balls Selecting. 373
11.3. Diagram of “Assignment Operation” during the Design of Proximity of Information Structure. 378
11.4. Variation Diagram of Proximity of Information Structure CovS(D’, D) (k = 3). 382
11.5. Calculation Processes of Information Coverage Cov (D’, D) and Information Redundancy Red (D’). 389
11.6. Calculation Time of Information Coverage Cov (D’,D) in Simulation Experiment (k = 10). 391
11.7. Comparison between Information Coverage and Information Redundancy of Three Review Extraction Results (k = 10, 20, 30). 398
12.1. Three Satisfaction Levels of Average User for Diverse Search Results. 405
12.2. Algorithm Pseudo-code of CovC-Select. 411
12.3. Extraction Process Diagram in Example 3. 413
12.4. Diagram of the Influence of Local Optimization on Greedy Algorithm. 415
12.5. Pseudo-code of CovSA-Select Algorithm. 416
12.6. Pseudo-code of FastCovSA-Select Algorithm. 421
12.7. Pseudo-code of CovRedSA-Select Algorithm. 423
13.1. Experimental Processing for Online Review Emotional Clustering. 432
13.2. The Average (a) and Highest (b) Performance of Each Clustering Algorithm on Each Dataset. 441
13.3. The Clustering Performance of Four Selected Clustering Algorithms on Taobao’s Real Online Reviews. 455
14.1. Graphical Model Representation of LDA. 468
14.2. Graphical Representation of the Proposed Semantic Search Framework. 471
14.3. Perplexity Results of the Online Reviews for Jinqianbao Restaurant on dianping.com. 477
14.4. Topic-discussion Hotness Changing Curve for the Topic “Poor Varieties of Food.” 477
15.1. Realization of IT Enterprises’ Value. 487
15.2. The Evolution, Definition and Relevant Study of BI&A. 489
15.3. Framework of DY Coal Group Enterprises. 491
15.4. DY Coal Group Strategic Positioning and Current Management and Control Mode. 492
15.5. BIS Model Implementation Framework of Resource-based Enterprise. 496
15.6. DY Coal Group Software Platform Architecture under BIS. 498
15.7. Comparison of the Implementation Situations of DY Coal Group under the BIS Model. 501
16.1. General Framework of Mobile Electronic Commerce. 514
16.2. The Characteristics of Mobile E-commerce and its Profit Growth. 514
17.1. Structure of Enterprises Business Intelligence System and Technical Features of Each Layer. 540
17.2. Traditional Statement System. 547
17.3. Overview Map for Statement of KTT. 548
17.4. The Query Interface of the Statement. 548
17.5. The Query Result Chart of the Statement. 549
17.6. The Derived Graph of the Statement. 549
17.7. The Chart of the Cockpit. 550
17.8. Data Display Interface. 550
17.9. Look for Reasons and Jump to Relevant Statements. 551
17.10. Reasons for Data Change. 551
18.1. The Chart of the Structure of the Witkey Commercial Pattern. 560
18.2. Categories of the Witkey Pattern. 561
18.3. The Commercial Pattern of the Platform of Socialized ­Campus-witkey. 563
18.4. Different Information Recommended to Users According to Different Users Eventually. 565
18.5. Key Business Process Diagram. 566

Tables

3.1. Membership and Corresponding Services. 41
3.2. Format of the Contract. 43
3.3. Historical Data of a Retail Store in the YNYY Pharmaceutical Chain. 54
5.1. Business Innovation Model of Tesla. 108
5.2. Comparison between XS Company’s Existing Models and B2S2C Model. 138
5.3. SWOT Analysis. 163
6.1. The Comparison of Business Models in Traditional Network and Social Network. 183
6.2. SWOT Analysis List of Renren. 192
6.3. Traditional Business Mode Features of Water Margin Community. 206
6.4. Information List of Water Margin Community. 207
6.5. Comparison of Water Margin Community’s Management Performance under Two Kinds of Models. 207
6.6. Business Model Adjustment Strategies of Water Margin Community under R-I Model. 208
9.1. Chinese Publications B2C Online Retail Market Share Proportion. 304
9.2. Parameter Estimates of Discrete System. 307
9.3. Parametric Statistics of Diffusion System. 307
9.4. The SWOT Analysis Results of Renren. 326
9.5. Fitting Results of R-I Model. 328
9.6. Regression Results after Adjustment. 333
11.1. Measure Values of Coverage of Information Content Based on Different Selection Results in Example 1. 376
11.2. Measure Values of Proximity of Information Structure Based on Different Selection Results in Example 1. 381
11.3. Measure Values of Information Coverage Based on Different Selection Results in Example 1. 384
11.4. Measure Values of Information Redundancy Based on Different Selection Results in Example 1. 387
11.5. Different Measure Values of Four Extraction Results in Example 2. 394
11.6. Statistics Description Information about Test Data of Online Users’ Product Review. 396
11.7. Statistics Information about Information Coverage and Information Redundancy of Different Review Extraction Results (k = 10, 20, 30). 397
11.8. t-Test Result of Comparison of Measure by Every Two Review Extraction Method (k = 10, 20, 30). 399
12.1. Paired t-Test Results for the Hypothesis of AvgScore(FastCovSA-Select) > AvgScore(Mi). 426
13.1. The Benchmarked Datasets Used in Our Experiments. 433
13.2. Different Types of Data Pre-processing. 435
13.3. Preliminary Notations for Term Weighting. 435
13.4. Term Weighting Models Used in Our Experiments. 436
13.5. The Clustering Algorithms Used in Our Experiments. 437
13.6. Confusion Matrix of Review Clustering. 440
13.7. The Percentage Difference (%) of Average Accuracy for Each Clustering Algorithm Over the Best Performance by Dataset. 442
13.8. The Percentage Difference (%) of the Highest Accuracy for Each Clustering Algorithm Over the Best Performance by Dataset. 442
13.9. Average and Best Performances for Clustering Algorithms Split into Two Groups. 443
13.10. Paired Comparative Results of Statistical Significance Tests for Each Clustering Algorithm on Clustering Accuracy. 444
13.11. Partitional Groups for Selected Clustering Algorithms Based on Performances. 445
13.12. The Percentage Difference (%) of Average Accuracy for Each Weighting Model Over the Best Performance by Dataset. 446
13.13. The Percentage Difference (%) of the Highest Accuracy for Each Weighting Model Over the Best Performance by Dataset. 446
13.14. The Percentage Difference (%) of Average Accuracy for Each Weighting Model on Four Superior Clustering Algorithms Over the Best Performance by Dataset.
447 13.15. Paired Comparative Results of Statistical Significance Tests for Each Weighting Model on Clustering Accuracy. 447
13.16. The Difference in Average Accuracy by Using Each Pre-processing Strategy by Dataset and Mean. 449
13.17. The Difference in the Highest Accuracy by Using Each Pre-processing Strategy by Dataset and Mean. 449
13.18. The Difference in Average Accuracy on Four Best Algorithms by Using Each Pre-processing Strategy by Dataset and Mean. 450
13.19. Paired Comparative Results of Statistical Significance Tests for Each Pre-processing Strategy on Clustering Accuracy. 450
13.20. The Percentage Difference (%) of Average Accuracy for Each Clustering Algorithm Over the Best Performance by New Unbalanced Dataset. 452
13.21. The Percentage Difference (%) of Highest Accuracy for Each Clustering Algorithm Over the Best Performance by New Unbalanced Dataset. 452
13.22. The Percentage Difference (%) of Average Accuracy for Each Weighting Model Over the Best Performance by New Unbalanced Dataset. 453
13.23. The Percentage Difference (%) of Highest Accuracy for Each Weighting Model Over the Best Performance by New Unbalanced Dataset. 453
13.24. Basic Statistic Description of Extracted Online Consumer Reviews. 454
15.1. Effectiveness of Informatization to the Strategy of Enterprises at the Organizational Level. 488
15.2. SWOT Analysis of Informatization Environment of DY Coal Group. 494
15.3. DY Coal Group Informatization Standard System Scope. 499
16.1. Profit Models of Mobile Internet. 514
16.2. Suggestion of YNYD Channel Layout. 523
16.3. YNYD Channel Deployment System. 524
18.1. The Comparison between Witkey and Other New Commercial Patterns. 563

Foreword

At the third meeting of the 12th National People’s Congress held on March 5, 2015, Premier Keqiang Li stated that the Chinese government under his leadership will “develop the ‘Internet Plus’ action plan to integrate the mobile internet, cloud computing, big data, and the Internet of Things with modern manufacturing, to encourage the healthy development of e-commerce, industrial networks, and internet banking, and to guide Internet-based companies to increase their presence in the international market.” Therefore, innovation 2.0 is the upgrading of innovation 1.0. Innovation 1.0 refers to innovations in the industrial era while innovation 2.0 refers to all forms of innovations in the information era and knowledge society.

The profound integration of the internet and traditional industries has led to the ongoing enhancement of the entire society’s innovative and productive powers and the birth of new forms of economic and social development as aided by the internet as both its infrastructure and its tool of realization, thus constantly creating new models, new industries and new economic norms. In present day China, internet plus has not only been applied to the service industry, creating such new conditions as internet finance, internet transportation, internet health, and internet education. Also it is beginning to combine with the primary and industrial sectors causing a series of innovative models and industries and economic norms such as internet plus industry, internet plus agriculture, internet plus manufacturing, internet plus financial services, and internet plus education. It is against this background that the publishing of this book E-Business Innovation and Case Study in the Internet+ Era meets the needs for economic development and talents in the internet era. In the book, the reader is not simply provided with a systematic array of basic concepts, theories and methodology, application innovations, and development trends in e-business. It is also hoped that the large number of application and project cases can help the understanding of innovative thinking and the development of innovative capabilities in e-business to provide practical help with innovation and entrepreneurship in e-business.

Internet+ and Electronic Business in China: Innovation and Applications consists of 18 chapters in four parts. The first part is theoretical foundations of e-business which includes basic concepts and mainstream theories regarding the definition of e-business, e-business models, e-business intelligence, e-business logistics, and e-business payment. The second part is internet plus innovation models in e-business which includes internet plus agriculture, social commerce, O2O, and internet finance. This part follows the theory plus cases then plus analysis pattern to provide a comprehensive and in-depth analysis of relevant cases to present mainstream e-business theories and trends of development.

The third part is about e-business platform application method innovations which includes application method innovation theories, application contexts and case analysis encompassing bilateral markets, e-business platform information search services, e-business platform information search service diversity assessment, e-business platform information search service diversity information extraction, emotional analysis of e-business online comments, and semantic search in e-business online comments.

Part four contains a careful selection of four actual e-business projects, which are internet plus resource enterprises, mobile internet, big data and business intelligence system, and social campus Witkey. From the perspective of project development, these e-business innovation projects are then analyzed in terms of the entire process of model analysis, design, and development to provide the readers with successful examples of implementing e-business entrepreneurship projects. As an example, “A Case Study of Mitubaba’s Social E-Business Model of Plateau Special Agricultural Products” as collected in this book is the only national special prize winner at China’s 2016 E-Business Case Summit Meeting and the National Top 100 E-Business Case Study Contest. Also included in the book are two-third prize winners. They are “Internet Plus Finance Case Studies Taking Lufax and Oriental Exchange as Examples” and “A Case Study of Social E-Business as Based on Campus Witkey Networks.”

Internet+ and Electronic Business in China: Innovation and Applications is compiled by Professor Qiongwei Ye from Yunnan University of Finance and Economics and Associate Professor Baojun Ma from Beijing University of Posts and Telecommunications. Also thanks to Associate Professor Nangai Yang and Lecturer Yanping Yu, both from Yunnan University of Finance and Economics, and Liu Yang from Emerald (China) for their language compilation.

The publication of Internet+ and Electronic Business in China: Innovation and Applications is sponsored Yunnan Province Young Academic and Technical Leader candidate Program (2018HB), Yunnan Provincial E-Business Crowd-Innovating Space (CIS, 2016, 2017DS012), Yunnan Provincial applied and Fundamental Key Research Project (2017FA034, 201601PG00002), Yunnan Provincial E-Business Experimental Teaching Demonstration Center (2015 High-Level College Practical Teaching Ability Enhancement Project; Yunnan Higher Education 2015), China’s National Natural Science Foundation Grant (71162005, 71402007, 71772017, 71362016, and 714021159), the Beijing Municipal Social Science Foundation (No. 17GLB009), and Key Laboratory of Electronic Commerce Innovation and Entrepreneurship in Yunnan Province (Yunnan Education Science 2014[16]).

Given the limited capabilities of the authors, there are bound to be limitations of different kinds. Any suggestions and feedback from colleagues and readers are much appreciated.

Manage cookies

We’re listening — tell us what you think

Join us on our journey