Blockchain-Empowered Halal Fashion Traceability System in Indonesia

Incorporating blockchain into Halal traceability systems is developing in nature; the research aspires to examine the participation intent in blockchain-empowered Halal fashion traceability (BHFT) system via a joint framework that includes diffusion of innovation theory, institutional theory, and Halal-oriented approach. The study uses a simple random sampling method to collect the data from 165 Indonesian Halal fashion manufacturing companies. PLS-SEM is employed to examine the conceptual framework. Findings show that Halal-oriented approach significantly affects institutional pressures, while institutional pressures significantly affects perceived desirability, and perceived desirability significantly affects the participation intent. The companies operating an inclusive Halal-oriented approach will be more aware of the institutional pressures that expect them to partake in a BHFT. The paper enhances the existing literature in Halal supply chains, blockchain, operation management, and information systems via a cohesive framework and empirical insight.

Multi-Objective Optimization Information Fusion and Its Applications for Logistics Centers Maximum Coverage

From past the development direction of logistics centers covering problem, the main solution is almost always relying on modern computer and gradually developed intelligent algorithm, at the same time, the previous understanding of dynamic covering location model is not "dynamic", in order to improve the unreasonable distribution of logistics centers deployment time, improve the service coverage, coverage as the optimization goal to logistics centers, logistics centers as well as each one can be free to move according to certain rules of "dot", according to the conditions set by the site moved to a more reasonable. The innovation of all algorithms in this paper lies in that the logistics centers themselves are regarded as the subject of free "activities", and they are allowed to move freely according to these rules by setting certain moving rules. Simulation results show that the algorithm has good coverage effect and can meet the requirements of logistics centers for coverage effect.

Construction and Optimization of Green Supply Chain Management Mode of Agricultural Enterprises in the Digital Economy

Digital economy is a rapidly developing economic form under the background of the information age. This article introduces the construction and optimization of the green supply chain management model of agricultural enterprises under the digital economy, and intends to provide some ideas and directions for the development of green supply chain management of agricultural enterprises based on digital economy. This paper proposes the construction and optimization research methods of the green supply chain management model of agricultural enterprises under the digital economy, including the overview of green supply chain management, the construction of the optimization management model of the green supply chain of agricultural enterprises, and the digital economy under the construction of a green supply chain management practice index system for agricultural enterprises. Experimental results show that average Cronbachα value of each scale factor of the optimized management model in this paper is 0.876, and optimized decision-making coordination mechanism has high internal consistency.

Automatic Equipment Design of Intelligent Manufacturing Flexible Production Line Based on Industrial Motorized Spindle

Based on the previous research on the production line automation, this paper carries out further research and further design and development on the basis of the original production line automation equipment. In this paper, the overall design of the automatic production line is carried out, and the various systems in the automatic production line are optimized, and the backward instruments are eliminated, and then some more advanced and convenient instruments are applied. Then, the hardware and software of the automatic production line are studied respectively, and the human-computer interaction module and real-time main control circuit module are re developed, and the electric shaft is applied to the automatic production line. Finally, the fuzzy PID controller of the stepping motor is designed. The experiment shows that the fuzzy PID control scheme is better than the traditional PID control scheme. After the rationalization of the system, the quality robustness of proactive planning is improved obviously. Then, the temperature of motorized spindle was tested.

Construction of e-commerce system based on 5G and Internet of Things technology

In order to improve the comprehensive performance of the e-commerce system, this paper combines 5G communication technology and the Internet of Things technology to improve the e-commerce system, and conduct end-point analysis on the e-commerce client data analysis system and smart logistics system. Moreover, this paper uses 5G technology to improve machine learning algorithms to process e-commerce back-end data and improve the efficiency of e-commerce client data processing. In addition, this paper combines the Internet of Things to build an e-commerce smart logistics system model to improve the overall efficiency of the logistics system. Finally, this paper combines the demand analysis to construct the functional module structure of the e-commerce system, and verifies the practical functions of the system through experimental research. From the experimental research results, it can be seen that the e-commerce system based on 5G communication technology and Internet of Things technology constructed in this paper is very reliable.

Supplier Evaluation and Selection System of Embedded E-Commerce Platform Based on Big Data

For e-commerce companies, it is easier to obtain a large amount of aggregated data about user behavior with the help of embedded network platforms, which contains valuable information that helps to form effective decision-making. This article first gives a detailed introduction to the evaluation and selection of e-commerce and suppliers; then puts forward the analytic hierarchy process and entropy method; finally, the AHP analytic method is used to build a supplier evaluation system and a selection system. The experimental results of this paper show that after obtaining the entropy AHP weights through the analytic hierarchy process, these 8 suppliers can be ranked and selected. Using the ABC classification method, classification is based on the ranking of suppliers. Among them, Class A suppliers account for 12.5%, which plays a key role in the construction of the evaluation and selection system of e-commerce suppliers.

Bayesian Belief Network Approach for Supply Risk Modelling

Today’s global and complex world increased the vulnerability to risks exponentially and organizations are compelled to develop effective risk management strategies for its mitigation. The prime focus of research is to design a supply risk model using Bayesian Belief Network bear in mind the tie-in of risk factors (i.e. objective and subjective) those are critical to a supply chain network. The proposed model can be re-engineered as per new information available at disclosure, so risk analysis will be current and relevant along the timeline as so situation is strained. The top three factors which influenced profitability were transportation risk and price risks. Netica is the platform used for designing and running simultaneous simulations on the Bayesian Network. The proposed methodology is demonstrated through a case study conducted in an Indian manufacturing supply chain taking inputs from supply chain/risk management experts. .

Decision and coordination of an O2O supply chain with market segmentation and showrooming effect

This paper investigates impacts of market segmentation and showrooming effect on the decision-making of an O2O supply chain, and puts forwards a contract to coordinate the O2O supply chain. Results show that, the showrooming effect is beneficial to the manufacturer, retailer and the supply chain, and the retailer will offer offline showrooming service. Under the influence of market segmentation, O2O supply chain is not necessarily better than single-channel supply chain structure. But adopting advertising and other means to improve consumers’ online channel acceptance, it can realize transformation from single-channel to O2O structure. The benefits of showrooming effect can eliminate the disadvantage of market segmentation. Moreover, a service cost sharing contract is put forward, which can perfectly coordinate the O2O supply chain with market segmentation and showrooming effect. These findings help managers to understand which channel structure is optimal by considering market segmentation and showrooming effect and identify possible pathways for them to perfectly cooperation.

Effect of Supply Chain Coordination on Performance

Research on supply chain management (SCM) focuses on “what” factors of a supply chain enable firms to achieve high performance. It examines the effect of two strategically important pillars: supply chain relationships or capabilities. However their isolated investigation leads to a limited understanding of “how” they can be combined to increase firm performance. In this study we argue that beyond their direct effects the relational and the capability-based determinants of a supply chain have a network of indirect relationships that concurrently and differentially affect firm performance. Building on the relational and resource-based views we develop a serial-mediation model examining the mediating effects of trust in supply chain and collaborative advantage (i.e. relational determinants), and supply chain agility and coordinated supply chain (i.e. capability-based determinants) of SCM. Through the use of hierarchical linear regression analysis we show that trust, agility and collaboration act as serial mediators that carry the indirect effect of coordination to firm performance.

Graph Database to Enhance Supply Chain Resilience for Industry 4.0

Supply chain network in the automotive industry has complex, interconnected, multiple-depth relationships. Recently, the volume of supply chain data increases significantly with Industry 4.0. The complex relationships and massive volume of supply chain data can cause visibility and scalability issues in big data analysis and result in less responsive and fragile inventory management. The authors develop a graph data modeling framework to address the computational problem of big supply chain data analysis. In addition, this paper introduces Time-to-Stockout analysis for supply chain resilience and shows how to compute it through a labeled property graph model. The computational result shows that the proposed graph data model is efficient for recursive and variable-length data in supply chain, and relationship-centric graph query language has capable of handling a wide range of business questions with impressive query time.