ArticleComputational intelligence and neuroscience2021
Performance Evaluation of Enterprise Supply Chain Management Based on the Discrete Hopfield Neural Network.
Article in Computational intelligence and neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Retracted: Performance Evaluation of Enterprise Supply Chain Management Based on the Discrete Hopfield Neural Network.Computational intelligence and neuroscience · 2023Article
- A Meta-Path-Based Evaluation Method for Enterprise Credit Risk.Computational intelligence and neuroscience · 2022Article
Corrections and comments
- Retraction · 2023-06-28Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In order to make up for the shortcomings of current performance evaluation methods, this paper proposes a new method of enterprise performance evaluation, discusses the construction principle of the evaluation index, and proposes a method of enterprise supply chain overall performance evaluation based on the discrete Hopfield neural network (DHNN) algorithm. Enterprise supply chain (SC) is an important way for enterprises to conduct business with other strategic partners in the market, and the improvement of SC performance is an important way to improve the core competitiveness of enterprises, so it is of great value to study the performance evaluation and index design of the enterprise SC. This method calculates the level value of the overall performance of the SC. This level value is a value between 0 and 1. The higher the value, the higher the overall performance level of the SC. Therefore, when evaluating the overall performance of the SC, appropriate index weights must be selected according to the characteristics of the industry, which helps to objectively evaluate the overall performance of the SC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.