Evidence map›Paper›PMID 38040843›Full record

ArticleScientific reports2023

Efficiency evaluation and nonlinear multi-objective optimization of forestry industry transformation in the Heilongjiang state-owned forest region.

Shuo Diao, Yude Geng

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Shuo DiaoCollege of Economics and Management, Northeast Forestry University, Harbin, 150040, China.
Yude GengCollege of Economics and Management, Northeast Forestry University, Harbin, 150040, China. gengyude@nefu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the deepening of the concept of sustainable development of the whole society, protecting forest resources has become a crucial task of the current society. The present forestry industrial structure of Heilongjiang state-owned forest areas has undergone significant changes, and the transformation of the forestry industry has become increasingly prominent. How to deepen the forestry industry transformation and improve its efficiency has become an important research direction in forest areas. This work first analyzes the data envelopment method, and further designs the evaluation method of forestry transformation efficiency in forest areas. Then, the evaluation index system of forestry industry transformation efficiency in Heilongjiang state-owned forest areas is built. The relevant nonlinear multi-objective optimization (MOO) constraints are designed. Relevant data are quoted to evaluate the efficiency of the forestry industry transformation in the Heilongjiang state-owned forest areas. The results show that: (1) During 2015-2021, the average value of the scale, technical, and comprehensive production efficiencies of Heilongjiang state-owned forest areas were 0.765, 0.53, and 0.399, all of which were less than 1. And they were in a relatively ineffective state. (2) The overall industrial transformation of state-owned forest areas was optimistic. The technical efficiency decreased slightly in 2017, while the pure technical efficiency was greater than 1 in 2016 and 2018. The efficiency value increased to the peak by the end of 2021. (3) In the transformation of the forestry industry in state-owned forest areas, the influence of the industrial economy and resource protection subsystems was the first and backward, and the contribution of the social development subsystem was in the middle. (4) In the MOO problem, the forest area should be planned according to the proportion of public welfare, multi-functional, and commercial forests: 35.2%, 38.8%, and 26%, respectively. This work provides an essential reference for protecting forest resources and contributes to the transformation and development of the social forestry industry.

Identifiers

PMID38040843
PMCPMC10692111

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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.