Evidence map›Paper›PMID 38510049›Full record

ArticleHeliyon2024

Mining the sustainability of takeaway businesses in online food delivery service supply chain.

Longxiao Li, Zusheng Zhang, Xixi Li, Jiafu Su, Yanling Jiang, Jun Cao, Fangsu Zhao

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

7 authors.

Longxiao LiSchool of Business Administration, Chongqing University of Science and Technology, No. 20, East University Town Road, Shapingba District, Chongqing, 401331, China.
Zusheng ZhangCollege of Mechanical and Vehicle Engineering, Chongqing University, No.174 Shazhengjie, Shapingba District, Chongqing, 400044, China.
Xixi LiTeaching Affairs Department, Chongqing Energy College, Chongqing, 402260, China.
Jiafu SuInternational College, Krirk University, Bangkok, 10220, Thailand.
Yanling JiangSchool of Business Administration, Chongqing University of Science and Technology, No. 20, East University Town Road, Shapingba District, Chongqing, 401331, China.
Jun CaoSchool of Business Administration, Chongqing University of Science and Technology, No. 20, East University Town Road, Shapingba District, Chongqing, 401331, China.
Fangsu ZhaoSchool of Business Administration, Chongqing University of Science and Technology, No. 20, East University Town Road, Shapingba District, Chongqing, 401331, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The online food delivery service supply chain constitutes a crucial element in achieving sustainable development goals. With its prosperity, an increasing number of takeaway businesses are drawn to this sector. As their numbers rise, issues such as profitability resilience, environmental friendliness, and fulfillment of social responsibility emerge, posing potential disruptions to the service supply chain. Against this backdrop, our endeavor is to mine the sustainability of takeaway businesses using the triple bottom line. We propose a two-stage approach involving the Bayesian best-worst method and a data mining technique to derive the weights of sustainability criteria and the clusters of takeaway businesses. Subsequently, a case study is conducted focusing on takeaway businesses on the

Indexed as

Bayesian best-worst methodHDBSCANOnline food deliveryService supply chainSustainability miningTakeaway businesses' sustainabilityTriple bottom line

Identifiers

PMID38510049
PMCPMC10950709

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.