Study on government subsidy in a two-level supply chain of direct-fired biomass power generation based on contract coordination

Kun Fan; Wenjin Mao; Hua Qu; Xinning Li; Meng Wang

doi:10.3934/jimo.2022049

Article Contents

2023, Volume 19, Issue 4: 2436-2451. Doi: 10.3934/jimo.2022049

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Study on government subsidy in a two-level supply chain of direct-fired biomass power generation based on contract coordination

1.
School of Economics and Management Beijing Forestry University, Beijing, 100091, China
2.
Neusoft Education Technology Group, Dalian Neusoft University of Information, Dalian, 116023, China
3.
School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, 450001, China

^*Corresponding author: Kun Fan
^*Corresponding author: Kun Fan

Received: August 2021

Revised: January 2022

Early access: April 2022

Published: April 2023

The research is supported by Ministry of Education Humanities and Social Sciences Foundation of China (No.21YJA630012)and Beijing Municipal Social Science Foundation (No.16GLC059)

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Abstract

Biomass power generation is helpful to build a clean, low-carbon, and green energy system, but the shortage of raw materials supply severely restricts the development of the biomass power generation industry in China. To solve problems of supply chain disharmony and low efficiency of government subsidy caused by stochastic factors in biomass power supply chain, this paper studies the decision-making of government subsidy on biomass power generation supply chain. First, a two-level supply chain model under stochastic supply and stochastic output environment is built. The two-level supply chain consists of farmers and the biomass power plant. Second, to achieve the coordination of the two-level supply chain through the calculation of the model, it sets up the combined contract model based on surplus compensation, shortage penalty, and revenue sharing. Then, the validity of the contract is demonstrated by the data obtained from the field survey. Finally, depending on the model and contract coordination results of the supply chain, the impacts of government subsidies on two members' decision-making are analyzed, and the changes of members' profits and chain's profits are discussed. Therefore, the government subsidy strategy for biomass direct-fired power generation is proposed.

Keywords:

Biomass direct combustion power generation,
contract coordination,
government subsidy.

Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

Citation:

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Figure 1. The expected profit of whole supply chain under centralized decision-making

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Figure 2. Expected profit of farmers and foresters and the biomass power plant respectly

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Figure 3. Profit of the supply chain under different subsidy distribution policies

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Table 1. Situation under different subsidy distribution policies when total subsidy value = 350

$ r_A $	$ r_B $	r	b	$ \lambda $	x	q
0	7/18	259	55	$ 13.64\% $	161135	173087
10	17/45	265	47	$ 11.63\% $	164141	173020
20	11/30	271	38	$ 9.52\% $	167091	172956
30	16/45	278	29	$ 7.32\% $	169989	172895
40	31/90	285	20	$ 5.00\% $	172838	172838
50	1/3	292	10	$ 2.56\% $	175639	172783

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Table 2. Situation under different subsidy distributions when total subsidy value = 200

$ r_A $	$ r_B $	$ E(\pi_A) $	$ E(\pi_B) $	$ E(\pi_C) $	x	q
0	2/9	2999732	18998304	21998036	155921	167486
10	19/90	2455410	18661118	21116528	158725	167310
20	1/5	1928749	18323116	20251865	161468	167135
30	17/90	1419743	17983412	19403156	164153	166959
40	8/45	928479	17641108	18569587	166783	166783
50	1/6	455139	17295277	17750416	169359	166605

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Table 3. Situation under different subsidy distribution policies

$ r_A $	$ r_B $	$ E(\pi_A) $	$ E(\pi_B) $	$ E(\pi_C) $	x	q
0	0	-1407826	-8916234	-10324060	144216	154913
10	0	-1116079	-8482206	-9598285	147293	155260
20	0	-843398	-8012288	-8855686	150340	155617
30	0	-592460	-7504496	-8096956	153361	155983
40	0	-366136	-6956586	-7322722	156358	156358
50	0	-167527	-6366028	-6533555	159334	156743
0	0.057	-310685	-1967673	-2278359	148015	158994
10	0.057	-178318	-1355214	-1533532	151145	159321
20	0.057	-73484	-698095	-771579	154244	159658
30	0.057	496	6284	6780	157314	160003
40	0.057	40045	760846	800891	160357	160357
50	0.057	41286	1568873	1610159	163376	160719
0	0.157	1675358	10610602	12285960	153230	164596
10	0.157	1518248	11538685	13056933	156431	164893
20	0.157	1318612	12526818	13845431	159597	165198
30	0.157	1072002	13578691	14650692	162729	165511
40	0.157	773601	14698425	15472027	165831	165831
50	0.157	418174	15890630	16308805	168905	166159
0	0.257	3712806	23514436	27227242	157182	168841
10	0.257	3257909	24760109	28018018	160434	169112
20	0.257	2745391	26081216	28826607	163647	169390
30	0.257	2169674	27482542	29652217	166824	169675
40	0.257	1524706	28969420	30494127	169967	169967
50	0.257	803889	30547792	31351681	173080	170266
0	0.357	5783661	36629858	42413519	160282	172171
10	0.357	5025561	38194268	43219829	163572	172420
20	0.357	4194682	39849485	44044167	166820	172676
30	0.357	3284320	41601399	44885719	170031	172937
40	0.357	2287187	43456554	45743741	173205	173205
50	0.357	1195321	45422232	46617553	176346	173479

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Table 4. Profit statement of biomass power plant under different subsidies when $ r_A $ = 20

$ r_B $	$ r_B+p_B $	x	Q	$ R(\pi_B) $	$ C(\pi_B) $	$ E(\pi_B) $	p
0	0.393	150340	155617	57988171	66000459	-8012288	-13.82%
0.007	0.4	150862	156157	59200760	66326206	-7125446	-12.04%
0.057	0.45	154244	159658	67808514	68506609	-698095	-1.03%
0.107	0.5	157120	162635	76338929	70475997	5862932	7.68%
0.157	0.55	159596	165198	84805198	72278380	12526818	14.77%
0.207	0.6	161753	167430	93218692	73947086	19271606	20.67%
0.257	0.65	163647	169390	101586998	75505782	26081216	25.67%
0.307	0.7	165324	171127	109917862	76974277	32943585	29.97%

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