Implementing a Big-Data Based C2B E-commerce in Agricultural Industry

DOI

10.2991/snce-18.2018.154How to use a DOI?

Keywords

Customer-to-business; Agricultural industry; Big-data techniques; Case based reasoning; Preferences calculation

Abstract

Recently, social networks and communication tools expose customer to extensive business information. This situation incurs higher customer requirements and rapidly changing market environments. Big-data and information technologies are introduced in business field for customer requirement analysis and preferences prediction, so as to respond to the rapidly changing business scenarios and achieve sustainable development. C2B is the reverse model of the traditional Business-to-Customer e-commerce strategy which enables consumers to name products or services such that the organization can generate the demand collection for a specific good or service. In China, current agricultural businesses are limited to B2C e-commerce which cannot accurately figure out urgent market requirements and predict consumer preferences. This situation cannot reverse farmers’ inferior position. With consideration of characteristics of agricultural industry, this project deals with agricultural issues with a conceptual e-commerce model named big-data based Customer-to-Business (BD-C2B). This model types big-data and information strategy perspectives to the farming industry and outputs scientific business perspectives, so as to support efficient and effective decision making processes. BD-C2B integrates continuous stream data, information and analytics with stored data, and to analyze stream data chunk-by-chunk while maintaining the continuity of context for farmers to run smarter, more agile e-business. Case based reasoning (CBR) is introduced in this model for logic predicate and propositional logic, which contributes to the likelihood and preferences calculation of new proposed products or services. Analytic hierarchy process (AHP) algorithm and an intuitionistic fuzzy based framework are introduced for evaluating the performance of this model.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiacong Zhao
AU  - Tingbin Chen
PY  - 2018/05
DA  - 2018/05
TI  - Implementing a Big-Data Based C2B E-commerce in Agricultural Industry
BT  - Proceedings of the 8th International Conference on Social Network, Communication and Education (SNCE 2018)
PB  - Atlantis Press
SP  - 753
EP  - 758
SN  - 2352-538X
UR  - https://doi.org/10.2991/snce-18.2018.154
DO  - 10.2991/snce-18.2018.154
ID  - Zhao2018/05
ER  -