Evidence map›Paper›PMID 40532033›Full record

ArticlePloS one2025

Improving the performance of the coffee supply chain using integrating fuzzy MCDM and simulation methods.

Ghazi M Magableh, Abdullah F Al-Dwairi, Ahmad Alhamouri

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ghazi M MagablehIndustrial Engineering Department, Yarmouk University, Irbid, Jordan.ORCID 0000-0002-3978-4127
Abdullah F Al-DwairiIndustrial Engineering Department, Jordan University of Science and Technology, Irbid, Jordan.ORCID 0000-0002-0614-0325
Ahmad AlhamouriIndustrial Engineering Department, Jordan University of Science and Technology, Irbid, Jordan.ORCID 0009-0009-3614-6267

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coffee is one of the drinks that are consumed worldwide. The global coffee beans industry is currently facing several challenges, including The COVID19 pandemic's long-term effects on their supply chains (SCs), adverse weather conditions affecting major coffee-producing regions, escalating price dynamics, and the increased in transportation costs. Jordan significantly relies on coffee imports, a critical agricultural product that constitutes an important part of local trade. Due to the lack of previous studies, the research aims to evaluate the current SC and improve Jordan's coffee SC performance by reducing lead time and shipping cost. The research first uses the combined Fuzzy Analytic Hierarchy Process (FAHP) and The Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the supplier and choose the best suppliers based on established criteria. Then, the research proposes an analysis with the goal of enhancing the efficiency of Jordan's coffee SC by applying Discrete Event Simulation (DES). Real company data is utilized to study, apply and evaluate the methodology used. The decision-making process employ decision makers and expert opinion input, providing a comprehensive and balanced evaluation of suppliers. Different scenarios are evaluated and compared based on the integrations of the FMCDM results in the simulation model. The findings identify the best and least favorable suppliers, highlighting Ethiopia's leadership in several indicators. The outcomes suggest reducing lead time and shipping costs, investing in technology, and establishing a culture of continuous improvement to improve efficiency, stability, and adapt to market conditions. The research provides a comprehensive analysis of the current state of the coffee SC and suggests opportunities for development. Finally, recommendations to improve the current coffee SC in Jordan and directions for future research are discussed.

Indexed as

CoffeeCommerceFood SupplyComputer SimulationCOVID-19Fuzzy LogicHumansJordanSARS-CoV-2Coffee

Identifiers

PMID40532033
PMCPMC12176285

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.