E-commerce logistics distribution mode in big-data context: A case analysis of JD.COM

Abstract This paper analyzes the existing distribution modes adopted by China's e-commerce enterprises. Based on the empirical analysis of the electronic mall at JD.com (Jing-Dong), this paper compares and investigates the different logistics distribution modes faced by e-commerce enterprises embracing the new features, new challenges, and new advantages of big data. The Analytic Hierarchy Process (AHP) method and entropy value are applied to investigate the e-commerce enterprise distribution choice mode and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is used to verify the model. Our research analysis and results bear strong managerial insights for e-commerce logistics distribution practitioners.

[1]  M. Casado,et al.  GAFAnomy (Google, Amazon, Facebook and Apple): The Big Four and the b-Ecosystem , 2016 .

[2]  G. Mehralian,et al.  Developing a coordination framework for pharmaceutical supply chain: using analytical hierarchy process , 2017 .

[3]  Yonggang Wen,et al.  Toward Scalable Systems for Big Data Analytics: A Technology Tutorial , 2014, IEEE Access.

[4]  Jianming Yao,et al.  Optimisation of one-stop delivery scheduling in online shopping based on the physical Internet , 2017, Int. J. Prod. Res..

[5]  Zelda B. Zabinsky,et al.  A multicriteria decision making model for reverse logistics using analytical hierarchy process , 2011 .

[6]  Aicha Aguezzoul,et al.  Third-party logistics selection problem: A literature review on criteria and methods , 2014 .

[7]  Diyar Akay,et al.  A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method , 2009, Expert Syst. Appl..

[8]  Marc Goetschalckx,et al.  Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms , 2002, Eur. J. Oper. Res..

[9]  Hing Kai Chan,et al.  Facilitating the Merger of Multinational Companies: A Case Study of the Global Virtual Enterprise , 2013, J. Glob. Inf. Manag..

[10]  Rudolf R. Sinkovics,et al.  Value co-creation in an outsourcing arrangement between manufacturers and third party logistics providers: resource commitment, innovation and collaboration , 2018 .

[11]  Dilpreet Singh,et al.  A survey on platforms for big data analytics , 2014, Journal of Big Data.

[12]  Kannan Govindan,et al.  Prioritizing the barriers to achieve sustainable consumption and production trends in supply chains using fuzzy Analytical Hierarchy Process , 2017 .

[13]  A. Marasco.  Third-party logistics: A literature review , 2008 .

[14]  Kannan Govindan,et al.  Interrelationships of risks faced by third party logistics service providers: A DEMATEL based approach , 2016 .

[15]  Tao Sun,et al.  E-commerce logistics distribution mode research , 2015, 2015 IEEE International Conference on Computational Intelligence & Communication Technology.

[16]  Bruce D. Weinberg,et al.  Perspectives on Big Data , 2013 .

[17]  Douglas J. Morrice,et al.  A Simulation Exercise to Illustrate the Impact of an Enterprise System on a Service Supply Chain , 2007, INFORMS Trans. Educ..

[18]  Thomas L. Saaty,et al.  Marketing Applications of the Analytic Hierarchy Process , 1980 .

[19]  P. Baker,et al.  The Handbook of Logistics and Distribution Management : Understanding the Supply Chain Ed. 6 , 2017 .

[20]  Xue Sun,et al.  E-Commerce Logistics Distribution Mode Analysis and Decision , 2015 .

[21]  A. Gunasekaran,et al.  Big data analytics in logistics and supply chain management: Certain investigations for research and applications , 2016 .

[22]  T.C.E. Cheng,et al.  Third-party purchase: An empirical study of third-party logistics providers in China , 2016 .

[23]  Jonathan Burton,et al.  Application of Analytical Hierarchy Process in Operations Management , 1990 .

[24]  Petri T. Helo,et al.  Big data applications in operations/supply-chain management: A literature review , 2016, Comput. Ind. Eng..

[25]  Sunil Tiwari,et al.  Big data analytics in supply chain management between 2010 and 2016: Insights to industries , 2018, Comput. Ind. Eng..

[26]  Kazim Sari,et al.  A modeling approach for evaluating green performance of a hotel supply chain , 2018, Technological Forecasting and Social Change.

[27]  Joseph Sarkis,et al.  Integrating and extending data and decision tools for sustainable third-party reverse logistics provider selection , 2019, Comput. Oper. Res..

[28]  Benjamin W. Wah,et al.  Significance and Challenges of Big Data Research , 2015, Big Data Res..

[29]  Wilfried Sihn,et al.  Structural concepts for horizontal cooperation to increase efficiency in logistics , 2011 .

[30]  Erik Brynjolfsson,et al.  Big data: the management revolution. , 2012, Harvard business review.

[31]  Ali Dag,et al.  An AHP-IFT Integrated Model for Performance Evaluation of E-Commerce Web Sites , 2018, Information Systems Frontiers.

[32]  Amy Z. Zeng,et al.  Developing a framework for evaluating the logistics costs in global sourcing processes , 2003 .

[33]  Rosário Macário,et al.  A Comprehensive Framework for Measuring Performance in a Third-party Logistics Provider , 2015 .

[34]  Peter Goos,et al.  Location of logistics companies : a stated preference study to disentangle the impact of accessibility , 2015 .

[35]  Ching-Fu Chen.  Applying the Analytical Hierarchy Process (AHP) Approach to Convention Site Selection , 2006 .

[36]  Ray Y. Zhong,et al.  E-commerce logistics in supply chain management: Implementations and future perspective in furniture industry , 2017, Ind. Manag. Data Syst..

[37]  Ching-Lai Hwang,et al.  Methods for Multiple Attribute Decision Making , 1981 .

[38]  Veljko M. Milutinovic,et al.  Paradigm Shift in Big Data SuperComputing: DataFlow vs. ControlFlow , 2014, Journal of Big Data.

[39]  Li Li,et al.  Customer satisfaction evaluation method for customized product development using Entropy weight and Analytic Hierarchy Process , 2014, Comput. Ind. Eng..

[40]  Amy J. C. Trappey,et al.  A one-stop logistic services framework supporting global supply chain collaboration , 2016 .

[41]  I. Gil-Saura,et al.  Antecedents and consequences of logistics value: And empirical investigation in the Spanish market , 2010 .

[42]  Gang Kou,et al.  Visualizing market structure through online product reviews: Integrate topic modeling, TOPSIS, and multi-dimensional scaling approaches , 2015, Electron. Commer. Res. Appl..

[43]  R. Yin.  Case Study Research: Design and Methods , 1984 .

[44]  Ajoy Kumar Dey,et al.  An analytical approach for selection of a logistics provider , 2010 .

[45]  Oscar F. Bustinza,et al.  Servitization, digitization and supply chain interdependency , 2017, Industrial Marketing Management.

[46]  Chin-Tsai Lin,et al.  Optimal marketing strategy: A decision-making with ANP and TOPSIS , 2010 .

[47]  G. Stephen Taylor,et al.  Modelling choice in logistics: a managerial guide and application , 2012 .

[48]  Gwo-Hshiung Tzeng,et al.  Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS , 2004, Eur. J. Oper. Res..

[49]  William Ho,et al.  The state-of-the-art integrations and applications of the analytic hierarchy process , 2017, Eur. J. Oper. Res..

[50]  Tsan-Ming Choi,et al.  Big Data Analytics in Operations Management , 2018 .

[51]  A. Rizzi,et al.  A fuzzy TOPSIS methodology to support outsourcing of logistics services , 2006 .

[52]  S. Hertz,et al.  Strategic development of third party logistics providers , 2003 .

[53]  Yu Liu,et al.  The Analysis of the Logistics Mode Decision to E-Commerce , 2012, J. Electron. Commer. Organ..

[54]  Jun-feng Bai,et al.  Research on the Selection of Business-to-Customer e-commerce Logistics Model Based on Analytic Hierarchy Process Method , 2017 .

[55]  Laura Meade,et al.  A conceptual model for selecting and evaluating third‐party reverse logistics providers , 2002 .

[56]  Gabriele Piccoli,et al.  Conceptualization, Operationalization, and Validation of the Digital Data Stream Readiness Index , 2018, J. Glob. Inf. Manag..

[57]  Ioannis Kopanakis,et al.  Big Data Analytics: Applications, Prospects and Challenges , 2018, Mobile Big Data.

[58]  Daniel D Prior,et al.  Examining Project Management Through a Marketing Lens: a Literature Review and Research Agenda , 2015 .

[59]  Tharam S. Dillon,et al.  T. Kapnoullas, A Virtual Logistics Network and an E-hub as a Competitive Approach for Small to Medium Size Companies , 2003, Human.Society@Internet 2003.

[60]  Wei Fan,et al.  Mining big data: current status, and forecast to the future , 2013, SKDD.

[61]  Chandra Prakash,et al.  Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment , 2015 .

[62]  M. Clarke.  Virtual logistics: An introduction and overview of the concepts , 1998 .

[63]  Ganesh Vaidyanathan,et al.  A framework for evaluating third-party logistics , 2005, CACM.

[64]  Thomas L. Saaty,et al.  Decision Making for Leaders: The Analytical Hierarchy Process for Decisions in a Complex World , 1982 .

[65]  Xiao Hong,et al.  B2C E-commerce Vehicle Delivery Model and Simulation , 2013 .