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Open Access

Crowd E-Home—A Crowd-Based Collaborative Decoration Platform

Rui Ge1Hongbo Sun1( )
School of Computer and Control Engineering, Yantai University, Yantai 264005, China
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Abstract

With the rapid development of Chinese urbanization and industrialization level, the Chinese real estate transaction area continues to grow, and the country's decoration industry is expanding. Due to the rapid expansion, the decoration industry has failed to establish a good industry order, and the current decoration industry has many problems, such as opaque information and low industrial efficiency. Traditional and Internet decoration companies have failed to solve these problems effectively. The purpose of this study is to build a new collaborative decoration platform to solve the shortcomings of the decoration industry and promote its healthy development. A crowd-based collaborative decoration platform called Crowd E-home is proposed. Based on the Building Information Modeling (BIM) of houses, the platform constructs collaborative intelligent digital models, which have the characteristics of evolution, coordination, multifaceted, and initiative. These models act as intermediate coordinators to complete the collaborative division of labor. This platform plays a role in matching multiparty transactions among consumers, designers, construction teams, material suppliers, and supervisors to solve the problem of the huge coordination costs of traditional decoration companies. It also breaks the space-time limit of consumer selection during the decoration process, improves the decision-making power of consumers, and meets consumer needs for personalized services. The collaborative concept of the platform and the application of BIM optimize the existing decoration industry chain, which transforms the traditional chain model into a star-shaped decoration closed-loop ecosystem.

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International Journal of Crowd Science
Pages 135-141

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Cite this article:
Ge R, Sun H. Crowd E-Home—A Crowd-Based Collaborative Decoration Platform. International Journal of Crowd Science, 2022, 6(3): 135-141. https://doi.org/10.26599/IJCS.2022.9100017

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Received: 29 December 2021
Revised: 29 April 2022
Accepted: 05 May 2022
Published: 09 August 2022
© The author(s) 2022

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).