Developing Information Sharing Model Using Cloud Computing and Smart Devices for SMEs Supply Chain

2017 ◽  
Vol 10 (3) ◽  
pp. 44-64 ◽  
Author(s):  
Chi-on Chan ◽  
Owen Liu ◽  
Ricky Szeto
Keyword(s):  
Cloud Computing ◽  
Supply Chain ◽  
Information Sharing ◽  
Size Distribution ◽  
Inventory Management ◽  
Supply And Demand ◽  
Smart Devices ◽  
Smart Device ◽  
Retail Stores ◽  
Demand Distribution

The mismatch between supply and demand always exists within the supply chain and among retail stores. This situation is even worse for SMEs who work without state-of-the-art technologies, especially in terms of quantitative demand and size distribution in fashion industry. In this paper, we develop a cloud computing and smart device (CCSD) model to address the stochastic deviation between supply and demand. A computational experiment proves that the performance of inventory management in the supply chain and among retail stores can be significantly improved by application of CCSD, irrespective of demand and size distribution. In this paper, we illustrate its benefits for both normal and right-skewed demand distribution. We find that different stages in supply chain can also be coordinated by using the CCSD platform. The results show that using all-channel communication network through CCSD increases the information sharing performance.

Developing Information Sharing Model Using Cloud Computing and Smart Devices for SMEs Supply Chain

2020 ◽  
pp. 791-812
Author(s):  
Chi-on Chan ◽  
Owen Liu ◽  
Ricky Szeto
Keyword(s):  
Cloud Computing ◽  
Supply Chain ◽  
Information Sharing ◽  
Size Distribution ◽  
Inventory Management ◽  
Supply And Demand ◽  
Smart Devices ◽  
Smart Device ◽  
Retail Stores ◽  
Fashion Industry

The mismatch between supply and demand always exists within the supply chain and among retail stores. This situation is even worse for SMEs who work without state-of-the-art technologies, especially in terms of quantitative demand and size distribution in fashion industry. In this paper, we develop a cloud computing and smart device (CCSD) model to address the stochastic deviation between supply and demand. A computational experiment proves that the performance of inventory management in the supply chain and among retail stores can be significantly improved by application of CCSD, irrespective of demand and size distribution. In this paper, we illustrate its benefits for both normal and right-skewed demand distribution. We find that different stages in supply chain can also be coordinated by using the CCSD platform. The results show that using all-channel communication network through CCSD increases the information sharing performance.

Coordination of elderly healthcare service supply chain with information asymmetry: Designs of option contracts under different demand distribution statuses

2020 ◽  
Vol 54 (5) ◽  
pp. 1291-1307
Author(s):  
Jun Zhao
Keyword(s):  
Supply Chain ◽  
Information Asymmetry ◽  
Information Sharing ◽  
Healthcare Service ◽  
Demand Distribution ◽  
Service Supply Chain ◽  
Option Contract ◽  
Demand Information ◽  
Continuous Demand ◽  
Elderly Healthcare

This paper studies the issue of demand information asymmetry in an elderly healthcare service (EHS) system represented by a two-echelon elderly healthcare service supply chain (EHSSC) comprising an elderly service integrator (ESI) and a service provider (ESP). The goal of the ESI is to decide on how much service capacity is required for placing orders to the ESP, who directly serves the customers. Considering discrete and continuous demand distribution statuses, a centralised model with symmetric demand information and decentralised models with asymmetric demand information are developed to analyse the optimal ordering decisions and discuss the influence of information asymmetry. Furthermore, option contracts are applied to help coordinate the supply chain under asymmetric demand information based on different demand distribution statuses. Optimal option contract menus are designed for the ESP to promote the information sharing. Results show that the option contract can coordinate the EHSSC with asymmetric demand information under both discrete and continuous demand distribution statuses. The exercise price will be higher under lower demand information than that under higher demand information and the transfer payment will be less under lower demand information than that under higher demand information. Moreover, although the ESI has demand information superiority and can make use of opportunistic behaviour to maximise its own profit, the ESP as the leader can design the option contract to incentive the ESI to achieve true information sharing, and even obtain nearly all of the channel profit.

A Research on Complex Event Processing Technology Based on Smart Logistic System

2014 ◽  
Vol 722 ◽  
pp. 430-435
Author(s):  
Bin Bin Fu ◽  
Jie Zhu
Keyword(s):  
Supply Chain ◽  
Inventory Management ◽  
Information Transfer ◽  
Supply And Demand ◽  
Complex Event Processing ◽  
Processing Technology ◽  
Event Processing ◽  
Supply Chain System ◽  
Technology Application ◽  
Demand Prediction

With IOT technology developing and the cost reducing, Its application in supply chain is a matter of time. Smart logistic system is one of the IOT technology application in supply chain which solve difficult problems, such as acquisition underlying data, information transfer and so on. we need to achieve higher level application and solve more complex problems such as improving inventory management accuracy, reducing supply chain management cost, improving accuracy of supply and demand prediction, supply chain's rapidly react ability,these need to use complex event processing technology. It will introduce how to apply complex event processing technology to supply chain system based on IOT. By this way we can sort out valuable information by processing a large number of simple event.

scholarly journals Supply Chain Inventory Collaborative Management and Information Sharing Mechanism Based on Cloud Computing and 5G Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Fuan Zhang ◽  
Zhenzhi Gong
Keyword(s):  
Cloud Computing ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Internet Of Things ◽  
Information Sharing ◽  
Bullwhip Effect ◽  
Collaborative Management ◽  
Computing Technology ◽  
Chain Management ◽  
Information Sharing Mechanism

With the development of economic globalization, the competition among enterprises is increasingly fierce. Therefore, companies need close information sharing to realize the integration of supply chain. This article aims to study the collaborative management and information sharing mechanism of supply chain inventory based on cloud computing and 5G Internet of Things. This article first introduces the theory and methods of collaborative supply chain management and the information exchange mechanism and then discusses the problem of information sharing in the supply chain, that is, the bullwhip phenomenon, and then from the demand forecast, supply chain structure, time lag, and shortage game, six aspects are analyzed. The cause of the bullwhip phenomenon is analyzed. Secondly, this article proposes a quantitative analysis of the bullwhip effect, establishes a mathematical model of the bullwhip effect in the supply chain, and uses quantitative analysis to analyze the value of information sharing in the supply chain. Finally, this article uses cloud computing technology to build a supply chain information collaboration system architecture and uses EPC Internet of Things to build a supply chain information sharing model and describes the entire operation process of the supply chain. The experimental results of this paper show that the application of cloud computing technology to supply chain management establishes a system platform for supply chain information sharing, improves the overall operational efficiency of supply chain management, and realizes supply chain information sharing and business collaboration. In addition, the operating costs and risks of each node enterprise in the supply chain are reduced by 12% compared with the nonsharing situation, which also shows that the overall benefits of the supply chain have been correspondingly improved and market competitiveness has been enhanced.

The Bullwhip Effect in Supply Chain and Countermeasures

2013 ◽  
Vol 711 ◽  
pp. 799-804 ◽  
Author(s):  
Yu Fang Chao
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Supply And Demand ◽  
Bullwhip Effect ◽  
Market Demand ◽  
Strategic Partnerships ◽  
Wide Spread ◽  
Demand Forecast ◽  
Demand Fluctuations ◽  
The Competitiveness Of Enterprises

As supply chain involves a wide spread of enterprises, it is inevitable to have a bullwhip effect. The reason, why bullwhip effect occurs, includes such factors as demand forecast, delay in delivery, bulk orders and others. Bullwhip effect results increased inventory, differences in supply and demand, posing great risks on enterprise operation. To reducing the bullwhip effect in supply chains, such strategies as establishing an information-sharing platform, establishing strategic partnerships, direct ship and transit, stabling market demand fluctuations, should be taken, which will improve the competitiveness of enterprises in supply chain.

scholarly journals Investigating Inventory Strategy Under Demand Distribution Fluctuation in Dual-Channel Supply Chain

2021 ◽  
Vol 8 ◽  
Author(s):  
Nai-Ru Xu ◽  
Jie Cheng ◽  
Zheng-Qun Cai
Keyword(s):  
Supply Chain ◽  
Inventory Management ◽  
Distribution System ◽  
Demand Uncertainty ◽  
Management Problem ◽  
Market Demand ◽  
Supply Chain System ◽  
Demand Distribution ◽  
Dual Channel ◽  
Dual Channel Supply Chain

When manufacturers construct a dual-channel distribution system, which includes online and offline sales channels, they need to solve the inventory management problem to ensure supply and reduce inventory costs of the supply chain system. The dual-channel supply chain is the research object, and the inventory decision model is designed to achieve optimal profit when market demand is divided into online and offline demands. The results of the numerical analysis and simulations, conducted using MATLAB, indicate that both the manufacturer and the retailer increase their inventories and that their profits decrease when demand uncertainty increases. Besides, the increase in the online demand ratio causes the increase in the manufacturer’s inventory and reduces the profits of the retailer and the entire supply chain.

scholarly journals Collaborative predictive business intelligence model for spare parts inventory replenishment

2015 ◽  
Vol 12 (3) ◽  
pp. 911-930 ◽  
Author(s):  
Nenad Stefanovic
Keyword(s):  
Data Mining ◽  
Supply Chain ◽  
Inventory Management ◽  
Business Intelligence ◽  
Supply And Demand ◽  
Real Data ◽  
Business Environment ◽  
Spare Parts ◽  
Data Set ◽  
Inventory Replenishment

In today?s volatile and turbulent business environment, supply chains face great challenges when making supply and demand decisions. Making optimal inventory replenishment decision became critical for successful supply chain management. Existing traditional inventory management approaches and technologies showed as inadequate for these tasks. Current business environment requires new methods that incorporate more intelligent technologies and tools capable to make fast, accurate and reliable predictions. This paper deals with data mining applications for the supply chain inventory management. It describes the unified business intelligence semantic model, coupled with a data warehouse to employ data mining technology to provide accurate and up-to-date information for better inventory management decisions and to deliver this information to relevant decision makers in a user-friendly manner. Experiments carried out with the real data set, from the automotive industry, showed very good accuracy and performance of the model which makes it suitable for collaborative and more informed inventory decision making.

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