International competition and trade conflict in a dual photovoltaic supply chain system

Journal Pre-proof International competition and trade conflict in a dual photovoltaic supply chain system Zhisong Chen, Shong-Iee Ivan Su PII:

S0960-1481(19)31778-1

DOI:

https://doi.org/10.1016/j.renene.2019.11.085

Reference:

RENE 12633

To appear in:

Renewable Energy

Received Date: 25 June 2019 Revised Date:

14 October 2019

Accepted Date: 15 November 2019

Please cite this article as: Chen Z, Ivan Su S-I, International competition and trade conflict in a dual photovoltaic supply chain system, Renewable Energy (2019), doi: https://doi.org/10.1016/ j.renene.2019.11.085. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

International Competition and Trade Conflict in a Dual Photovoltaic Supply Chain System

Zhisong Chen Business School, Nanjing Normal University, Qixia District, Nanjing 210023, China Stern School of Business, New York University, 44 West Fourth Street, New York, NY 10012, USA E-Mail: [email protected]

Shong-Iee Ivan Su Supply Chain and Logistics Management Research Lab, Department of Business Administration, School of Business, Soochow University, Taipei E-Mail: [email protected]

Abstract: This study has explored a contemporary trade conflict issue heated up by the trade war between two largest economies in the world. Since the solar industry is a fast developing and critical renewable energy industry sector with many global suppliers competing fiercely in the world market, a dual international competing PV module supply chain system is conceptualized to conduct a game-theoretical modeling study for the exploration. Four modeling scenarios including Free Trade (FT), Trade Protection (TP), Price Discrimination (PD) and Anti-price Discrimination (AD) are investigated. A real world–based dual international competing PV supply chain system is designed for the numerical and sensitivity analyses. Two key findings from the study can be summarized: (1) Price discrimination strategy can create the most total supply chain profits and social welfares for dual international competing supply chains but this strategy will eventually lead to trade protection of the importing country and erode the supply chain profits and social welfares; (2) Trade Protection policy delivers the lowest total social welfares and demands for the dual international competing supply chains. The findings imply that in a dual international competing PV supply chain system, Free Trade policy would be the most appropriate trade policy to take by both governments and supply chains for the development of a sustainable solar energy sector. However, human systems are imperfect. The key finding also echoes the recent turbulence development of the world trade conflict that any unfair trade policy will benefit only the country who exercises the unfair trade policy that eventually leads to escalating trade conflict and brings economic damages to the trading stakeholders. Thus, an even more critical issue to explore is to find ways to resolve trade conflict at the early stage of trade conflict, such as the trade protection stage, before the conflict is worsening to the most serious conflict stage and cause serious economic and political damages to the involved parties and the world. This would be an important and emergent research subject to be explored. Keywords: Photovoltaic (PV) Supply Chain; International Competition; Trade Conflict; Free Trade; Price Discrimination; Trade Protection.

1

International Competition and Trade Conflict in a Dual Photovoltaic Supply

2

Chain System

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Abstract: This study has explored a contemporary trade conflict issue heated up by the trade war between two

26 27

Keywords: Photovoltaic (PV) Supply Chain; International Competition; Trade Conflict; Free Trade; Price

largest economies in the world. Since the solar industry is a fast developing and critical renewable energy industry sector with many global suppliers competing fiercely in the world market, a dual international competing PV module supply chain system is conceptualized to conduct a game-theoretical modeling study for the exploration. Four modeling scenarios including Free Trade (FT), Trade Protection (TP), Price Discrimination (PD) and Anti-price Discrimination (AD) are investigated. A real world–based dual international competing PV supply chain system is designed for the numerical and sensitivity analyses. Two key findings from the study can be summarized: (1) Price discrimination strategy can create the most total supply chain profits and social welfares for dual international competing supply chains but this strategy will eventually lead to trade protection of the importing country and erode the supply chain profits and social welfares; (2) Trade Protection policy delivers the lowest total social welfares and demands for the dual international competing supply chains. The findings imply that in a dual international competing PV supply chain system, Free Trade policy would be the most appropriate trade policy to take by both governments and supply chains for the development of a sustainable solar energy sector. However, human systems are imperfect. The key finding also echoes the recent turbulence development of the world trade conflict that any unfair trade policy will benefit only the country who exercises the unfair trade policy that eventually leads to escalating trade conflict and brings economic damages to the trading stakeholders. Thus, an even more critical issue to explore is to find ways to resolve trade conflict at the early stage of trade conflict, such as the trade protection stage, before the conflict is worsening to the most serious conflict stage and cause serious economic and political damages to the involved parties and the world. This would be an important and emergent research subject to be explored.

Discrimination; Trade Protection.

28 29

1

1

1. Introduction

2

In 2017, the U.S. solar industry was expected to be a casualty in Donald Trump’s

3

trade war. In January, the U.S. slapped a 30% tariff on imported solar cells and

4

modules (also known as panels). The tariffs on China’s solar industry were expected

5

to raise solar panel prices, and depress new installations for years to come. However,

6

the final impact of the tariffs is largely inconsequential. Federal tax credits, state

7

renewable energy goals, and plunging prices for equipment from China have driven

8

healthy demand despite the import duties. Furthermore, the Chinese slashed domestic

9

subsidies for the solar industry and was moving utility-scale solar to competitive

10

bidding. That elicited cut-throat competition between rival firms, flooding the global

11

market, and sending PV module prices plunging to their lowest level ever. Industry

12

expert is seeing the pipeline of utility-scale solar projects to be built in 2019-2020

13

accelerating for the industry as a whole (Coren, 2018).

14

Starting from a 30% tariff imposed on foreign-made solar cells and components

15

by Trump government since February 7, 2018, with the tariffs declining to 15% by the

16

fourth year (Milman, 2018; Reuters, 2018), Trump announced his intention to enforce

17

a 25% tariff on steel and a 10% tariff on aluminum imports on March 1, 2018

18

(Diamond, 2018). Very Soon, a tit-for-tat tariff countermeasure by the Chinese

19

government was going into effect on March 23, 2018 on about $3 billion worth of US

20

imports, hitting 128 products ranging from pork, meat and fruit to steel pipes (Shane,

21

2018).

22

On April 3, 2018, the Trump administration threatened to slap stiff tariffs on

23

some $50 billion in Chinese imports across 1,300 categories of products (Davis et al.,

24

2018). On April 4, 2018, China’s State Council unveiled a list of products worth $50

25

billion imported from the United States that will be subject to a 25% tariff (Xinhua,

26

2018). On May 3, 2018, the National Taxpayers Union delivered an open letter to

27

President Trump and Congress that was signed by over 1,100 economists from left,

28

right, up, down, and center urging him to reconsider American tariff policy. It’s an

29

echo of the letter signed by 1,028 economists in 1930 opposing the Smoot-Hawley

30

tariff (Carden, 2018). 2

1

However, on June 15, 2018, Trump approved tariffs on $50 billion of Chinese

2

goods (Bloomberg News, 2018); on the same day, after Trump kicked off trade war,

3

China’s Finance Ministry imposed an additional 25% tariff on some US $50 billion of

4

US imports to strike back (Delaney et al., 2018). On August 7, 2018, U.S. Trade

5

Representative Robert Lighthizer confirmed 25% tariffs on $16 billion worth of goods

6

from China, as the second round of import duties imposed under the Section 301

7

process, effective August 23. Solar cells and modules are included in this list and

8

these 25% tariffs will add to the 30% Section 201 import duties, meaning an effective

9

85% tariff on any solar cells or modules imported into the United States from China

10

after two rounds of anti-dumping and countervailing duties imposed on Chinese solar

11

products in 2012 and 2014 (Roselund, 2018).

12

Under the background of U.S.-China trade war, it is important to investigate the

13

pricing strategies of an international competing supply chain in the photovoltaic (PV)

14

industry to explore the price discrimination and tariff imposing impact on dual

15

international competing PV supply chains. Two key issues will be addressed in this

16

study: (1) from a PV supply chain perspective, should an exporting PV supply chain

17

adopt a price discrimination strategy to pursue more profits in its foreign market?

18

Second, should a government impose tariff on an importing PV supply chain adopting

19

a price discrimination strategy? These questions will be explored through a two-stage

20

game and bargaining theoretical modeling approach with a numerical and sensitivity

21

analysis to better understand how the key operational decisions and their supply chain

22

financial performances and the corresponding social welfares will be impacted.

23

In the following sections, the corresponding literatures are first reviewed in

24

section 2; the notations and overview for the dual international competing PV supply

25

chains with anti-price discrimination for this study are defined in section 3; the

26

game-theoretical models for the international competition of dual PV supply chains

27

under four different scenarios are developed, analyzed and compared in section 4,

28

including baseline free trade scenario (section 4.1), trade protection scenario (section

29

4.2), price discrimination scenario (section 4.3), and anti-price discrimination scenario

30

(section 4.4); the numerical and sensitive analysis of a hypothetical case for all 3

1

analytical models are conducted and the results and comparisons are synthesized in

2

section 5; the managerial insights and policy implications are discussed and

3

summarized in section 6; and the research contributions and foresights from this study

4

are synthesized and concluded in the final section.

5 6

2. Literature Review

7

Recent literatures regarding trade war and conflict are first reviewed. Miyagiwa

8

et al. (2016) presented a dynamic model of trade wars in contingent protection using

9

World Bank data of worldwide anti-dumping filings during the years 1995–2014 and

10

tested the importance of “relative market size” in understanding recent patterns of

11

anti-dumping filings and contingent protection in world trade. Robert (2017)

12

commented on the coming solar trade war and discussed the tariffs and prices on solar

13

PV industry of the United States and found that higher prices would lead to decreased

14

demand and fewer jobs. Robinson et al. (2018) explored the implications of a collapse

15

of NAFTA and potential disintegration of the North American trade bloc with a

16

multi-country, multisector CGE model of global trade (GLOBE model), discussed

17

different models used for NAFTA scenarios and concluded that a trade war in North

18

America is not in the interests of any of the participants.

19

Virginia (2018) analyzed the U.S. trade and issues related to its major trading

20

partners and the new protectionist measures initiated by president Trump, alongside

21

the domestic and international responses and concluded that rather than triggering a

22

global trade war, the Trump administration is preparing the means to exert pressure to

23

renegotiate U.S. trade agreements. Guo et al. (2018) showed that a trade war triggered

24

by high U.S. import tariffs will lead to a collapse in U.S.-China bilateral trade and

25

will make the United States experience large social welfare losses, whereas China

26

may lose or gain slightly depending on the effect of trade war on U.S.-China trade

27

balance. Li et al. (2018) used a multi-country global general equilibrium (GE) model

28

to numerically simulate the effects of possible China–U.S. trade wars, and the

29

research results show that China will be significantly hurt by China–U.S. trade war

30

but negative impacts are tolerable. U.S. can gain under unilateral sanction measures to 4

1

China, but will lose if China takes retaliation measures. Buongiorno et al. (2018)

2

estimated the potential impact of prohibitive import barriers in U.S. and of

3

countervailing measures abroad on the economic welfare of consumers and producers

4

on the forest sector of U.S. and the rest of the world. The research found that a trade

5

war initiated by prohibitive U.S. protectionist policies would decrease the total

6

welfare of most countries involved. Kimberly (2018) analyzed the trade war from the

7

domestic and international situation in U.S. and concluded that Trump and his trade

8

hawks may be winning the internal policy wars but the losers will outnumber the

9

winners across U.S.

10

Literatures regarding the impacts of trade war on the supply chain operations are

11

also reviewed. Isakson (2008) studied whether anti-dumping measures were suited for

12

modern globalized trade with consumer goods and concluded that anti-dumping

13

decisions must take economic growth more into consideration. Monahan et al. (2017)

14

pointed out that the Trump administration should take a broad suite of tools to

15

effectively manage a supply chain to implement the trade and treaty reform. Meckling

16

et al. (2017) studied how firms' participation in global supply chains affected their

17

trade preferences. The research result shows that multinational corporations tend to

18

prefer open trade while domestic import competing firms favor trade protection.

19

Many literatures investigated the competition issues among supply chains. Ha

20

and Tong (2008) investigated contracting and information sharing in two competing

21

supply chains with different investment costs for information sharing. Wu et al. (2009)

22

explored the equilibrium behavior of two competing supply chains in the presence of

23

demand uncertainty. Zhao and Shi (2011) studied the supply chain structure and

24

contracting strategy for the two competing supply chains. Xie et al. (2011) studied the

25

selection of supply chain structures and quality improvement strategies of the two

26

competing supply chains. Rezapour et al. (2011a) proposed a model for designing the

27

network of a new entrant supply chain under inelastic demand and in the presence of

28

pre-existing competing chains. Rezapour et al. (2011b) developed duopolistic

29

competitive supply chain network models with sequential acting and variable

30

delivered prices. Ha et al. (2011) studied the incentive for vertical information sharing 5

1

in competing supply chains with production technologies that exhibit diseconomies of

2

scale.

3

Chen et al. (2012) investigated pricing decisions and information value in two

4

competing supply chains. Sheu et al. (2013) investigated the impact of bargaining

5

power on negotiations between manufacturers and reverse logistics providers in

6

competing reverse supply chains under the government intervention. Wu (2013)

7

examined the impact of buyback policy on retail price, order quantity and wholesale

8

price in a duopoly of two competing supply chains under the competing supply chain

9

framework. Li et al. (2013) investigated the equilibrium contract strategies of two

10

competing supply chains, compared the outcomes obtained from different scenarios

11

and studied the impact of competition density and risk attitudes on the suppliers'

12

contract choices. Zhang and Yang (2013) provided the outcome of centralized

13

equilibrium, prisoner's dilemma equilibrium, and decentralized equilibrium under

14

different decision models with regards to bilateral competing supply chain system.

15

Liu et al. (2014) examined the efficacy of cost sharing in a model of two

16

competing supply chains and evaluated the implications of advertising strategy for

17

overall supply chain efficiency and consumer welfare. Wei and Zhao (2015)

18

developed five game decision models to study the pricing and remanufacturing

19

decisions in a duopoly market with two competing supply chains. Taleizadeh et al.

20

(2016) studied the optimal selling prices and order quantities for the two competing

21

supply chains in the presence of different composite coordinating strategies. Shamir

22

and Shin (2016) examined the public forecast information sharing in a market

23

comprised of an incumbent supply chain facing the possible entry of a competing

24

supply chain. Ha et al. (2017) analyzed the impact of the decision making on demand

25

information sharing in two competing supply chains. Zhang and Wang (2017) studied

26

a price competition model of two competing supply chains, adopting two-stage

27

Stackelberg game under the condition of incomplete knowledge. Chen and Su (2017)

28

explored the dual PV supply chains under the Bertrand competition assumption by

29

three game-theoretical modeling scenarios considering the public subsidy from a

30

social welfare maximization perspective. 6

1

Xiao et al. (2018) developed two duopoly game models to explore price

2

decisions and the channel benefit of decentralization for two competing supply chains

3

and investigated the channel structure decisions in the presence of fixed marketing

4

and manufacturing costs. Wei et al. (2018) studied the effect of dual-channel format

5

on supply chain’s competition ability and the effect of different bargaining powers on

6

the competition between two supply chains and the optimal pricing decisions of all

7

supply chain members when one supply chain introduced an online retailing channel.

8

Chen and Su (2018) went beyond two competing supply chains and studied multiple

9

PV supply chains under Cournot competition with three game-theoretical models.

10

The above reviewed literatures, nevertheless, do not explore a highly

11

contemporary issue relating to the price discrimination and countering tariff imposing

12

in the international trade market. In the face of research shortfall identified in the

13

existing literatures, the cooperative decision models for dual international competing

14

PV supply chains under four different scenarios are developed, analyzed and

15

compared to explore how the price discrimination strategies in a dual international

16

competing PV supply chain system are affected by the anti-price discrimination tariff

17

policies of the importing country regarding the supply chain performances.

18 19 20

3. Notation and Assumption for Dual International Competing Photovoltaic Supply Chains

21

Based on the recent PV product trade information and literature, a dual

22

international competing photovoltaic (PV) supply chain system with anti-price

23

discrimination, i.e. anti-dumping tariff imposing, is conceptualized in Figure 1.

7

1 2

Figure 1 Dual international competing PV supply chains with anti-price discrimination

3 4

There are two PV supply chains in the international trading system. Both supply

5

chains offer PV module products and corresponding services, however, PV supply

6

chain 1 sells in not only its home market (market 1) but also its foreign market

7

(market 2) while PV supply chain 2 only sells in its home market (market 2). Thus,

8

PV supply chain 1 and 2 compete only in market 2. To protect the PV industry, the

9

government of importing country (government 2) may impose anti-price

10

discrimination (anti-dumping) tariffs on PV module products imported from PV

11

supply chain 1 if PV supply chain 1 adopts an aggressive price discrimination strategy

12

and is identified as an unfair competition by government 2.

13

Four modeling scenarios from free trade to escalated trade conflicts will be

14

investigated for this study: (1) Free Trade (FT): PV supply chain 1 does not adopt a

15

price discrimination strategy for its export and government 2 does not impose any

16

tariff on PV module products imported PV supply chain 1. This is the baseline

17

scenario as the base for analysis comparison.; (2) Trade Protection (TP): PV supply

18

chain 1 does not adopt any price discrimination strategy but government 2 imposes a

19

tariff on PV module products imported from PV supply chain 1; (3) Price

20

Discrimination (PD): PV supply chain 1 adopts a price discrimination strategy while

21

government 2 does not impose any tariff on imported PV module products from PV

22

supply chain 1; and (4) Anti-price Discrimination (AD): PV supply chain 1 adopts a

23

price discrimination strategy and government 2 retaliates by imposing a tariff on 8

1

imported PV module products from PV supply chain 1.

2

For the purpose of modeling, the following parameters are defined. The unit costs

3

of C-Si materials for supplier 1 and 2 are c1 and c 2 . The unit processing costs of PV

4

module products for manufacturer 1 and 2 are c01 and c02 . The unit logistics cost of

5

PV module products exported from country 1 to country 2 is l . The C-Si materials are

6

supplied from supplier 1 to manufacturer 1 with wholesale price w1 , and the C-Si

7

materials are supplied from supplier 2 to manufacturer 2 with wholesale price w2 . PV

8

module products are sold by manufacturer 1 to its domestic market (market 1) with

9

retail price p1 and to its foreign market (market 2) with retail price ϕ p1 , where

10

ϕ ∈ ( 0,1] is the price discrimination parameter. PV module products are sold by

11

manufacturer 2 only to its domestic market (market 2) with retail price p2 . The

12

domestic ordering quantity (demand) of PV module products for manufacturer 1 is

13

q11 and the foreign ordering quantity (demand) is q12 . The domestic ordering

14

quantity (demand) of PV module products for manufacturer 2 is q2 . Let q12FT , q12TP ,

15

q12PD and q12AD be the foreign ordering quantities of manufacturer 1 under the baseline,

16

trade protection, price discrimination and anti-price discrimination scenarios

17

respectively. Let ∆ q12 be the foreign ordering quantity difference between the

18

baseline scenario and one of the four scenarios. Then, under the baseline scenario,

19

TP ∆ q12 = q12FT − q12FT = 0 ; under the trade protection scenario, ∆ q12 = q12 − q12FT < 0 ;

20

under the price discrimination scenario, ∆ q12 = q12PD − q12FT > 0 ;

21

anti-price discrimination scenario, ∆ q12 may be equal, larger, or smaller than 0

22

depending upon the scale of price discrimination and retaliating tariff, i.e.

23

∆ q12 = q12AD − q12FT >=< 0 .

and under the

24

Based on the market demand characteristics of PV module products, there is a

25

reverse relationship between the demand of PV module products and the retail price 9

1

of PV module products. Thus, manufacturer 1’s demand functions of PV module

2

products in domestic market (market 1) and foreign market (market 2) can

3

respectively be defined as: q11 ( p1 ) = a11 − bp1 and q12 ( p1, p2 ) = a12 − bϕ p1 + dp2 . Let

4

a1 = a11 + a12 , then, manufacturer 1’s total demand function of PV module products in

5

both

6

q1 ( p1 , p2 ) = q11 ( p1 ) + q12 ( p1 , p2 ) = a1 − (1 + ϕ ) bp1 + dp2 . Likewise, manufacturer 2’s

7

demand function of PV module products in domestic market (market 2) is given by

8

q2 ( p2 , p1 ) = a2 − bp2 + dϕ p1 . Hereinto, a11 , a12 , a1 and a 2 are the choke quantity of

9

the demand function; b is the reaction extent of the ordering quantity (demand) with

10

respect to (w.r.t.) the change of retail price; and d is the reaction extent of the

11

ordering quantity (demand) w.r.t. the change of competitor’s retail price. Government

12

2 (importing country) may impose tariffs τ p1 on PV module products imported from

13

PV supply chain 1, where τ is the tariff rate and τ > 0 . Two suppliers’ bargaining

14

powers are set at the same level, λ .

domestic

and

foreign

markets

is

15

Based on the aforementioned assumptions, the profit functions of C-Si supplier 1,

16

PV module manufacturer 1 and PV supply chain 1 are represented respectively as

17

follows:

18

Π S1 ( w1 ) = ( w1 − c1 ) q1 ( p1 , p2 )

19

Π M1 ( p1 , p2 ) = p1q11 ( p1 , p2 ) + (ϕ − τ ) p1 − l  q12 ( p1 , p2 ) − ( w1 + c01 ) q1 ( p1 , p2 )

20

Π SC1 ( p1 , p2 ) = p1q11 ( p1 , p2 ) + (ϕ − τ ) p1 − l  q12 ( p1 , p2 ) − ( c1 + c01 ) q1 ( p1 , p2 )

21

And also, the profit functions of C-Si supplier 2, PV module manufacturer 2 and

22

PV supply chain 2 are represented respectively as follows:

23

Π S2 ( w2 ) = ( w2 − c2 ) q2 ( p2 , p1 )

24

Π M 2 ( p2 , p1 ) =  p2 − ( w2 + c02 )  q2 ( p2 , p1 )

25

Π SC2 ( p2 , p1 ) =  p2 − ( c2 + c02 )  q2 ( p2 , p1 )

26

According to the classical economics theory (Mankiw, 2011), the social welfare 10

1

2

3 4 5 6

function

SW1

for market 1 can be expressed as follows: 1 − 2 (1 − ϕ + τ ) 2 1  (ϕ − τ )( a11 − q11 ) − b ( c1 + c 01 + l )  q1 + q11 b 2b 1 1 + 2 + 2 1−ϕ +τ  + a11 + l  q11 + η  ( ∆ q12 )  − κ  ( − ∆ q12 )    b 2  2   

SW1 ( q11 , q12 ) =

where η is the coefficient of price-discrimination damage and κ is the coefficient of trade-protection damage. Following Singh and Vives (1984), the social welfare function SW2 for market 2 can be expressed as follows: SW2 ( q12 , q2 ) =

7

1 1   ( ba12 + da2 ) q12 + ϕ ( ba2 + da12 ) q2  − bq122 + (1 + ϕ ) dq12 q2 + ϕbq22   2  2 ϕ (b − d )  

−

2

ϕ −τ b

1 + ( a11 − q11 ) q12 − ( c2 + c02 ) q2 − η ( ∆q12 )  2

2

1 + 2 + κ ( −∆q12 )   2 

8

It is assumed that the supplier and manufacturer in each PV supply chain bargain

9

over the wholesale price of C-Si materials using Nash Bargaining mechanism (Nash,

10

1950; Kalai & Smorodinsky,1975; Binmore et al.,1986; Muthoo, 1999) to achieve

11

cooperation and dual PV supply chains compete in a Bertrand way (Bertrand, 1883;

12

Edgeworth, 1889; Salop & Stiglitz, 1977; Dixon, 1984), i.e. the dual PV supply

13

chains compete on the retail price of PV modules they sell and make pricing decisions

14

independently but at the same time.

15 16

4. Dual International Competing PV Supply Chain Modeling

17

This section will develop the game-theoretical models for the four modeling

18

scenarios and the mathematical functions of the analytical results will be summarized

19

in Table 1 at the last part of this section.

20

4.1 Free Trade Baseline Scenario ( τ

= 0, ϕ = 1, κ = 0,η = 0 )

21

In the free trade baseline scenario, PV supply chain 1 will not implement any

22

price discrimination strategy when exporting PV module products to Country 2, i.e.,

23

ϕ = 1 . Its domestic retail price of unit PV module product equals to the retail price in

24

the foreign market; and Country 2 will not impose any tariff on PV module products

25

imported from Country 1 to protect its own industries, i.e., 11

τ =0.

The decision

1

sequence is as follows: Firstly, the C-Si supplier S1 and the C-Si module manufacturer

2

M1 in the exporting Country 1 cooperate with each other via Nash bargaining

3

mechanism, i.e., S1 and M1 bargain over the wholesale price of the module to achieve

4

a cooperation within PV supply chain 1, so does S2 and M2 within PV supply chain 2

5

in the importing Country 2; then, PV supply chain 1 sets its domestic and foreign

6

retail price of PV module product to maximize its profit, so does PV supply chain 2 in

7

the importing Country 2; finally, the price competition between M1 and M2 occurs in

8

the importing Country 2’s PV market. The Stackelberg game-Nash bargaining model

9

for the dual competing PV supply chains can be formulated as (Superscript o: free

10

trade baseline scenario):

11

 max  Π w , p o , p o  λ Π w , p o , p o 1−λ  w1  S1 ( 1 1 2 )  M1 ( 1 1 2 )  o o o o o  s.t. Π S1 ( w1 , p1 , p2 ) + Π M1 ( w1 , p1 , p2 ) = Π SC1  1− λ λ  max  Π S2 ( w2 , p2o , p1o )   Π M 2 ( w2 , p2o , p1o )       w2  s.t. Π S ( w2 , p2o , p1o ) + Π M ( w2 , p2o , p1o ) = Π oSC 2 2 2  o o o o  p1 , p2 , Π SC and Π SC are derived from solving the following problem 1 2    max Π SC1 ( p1 , p2 )   p1   max Π SC ( p2 , p1 ) 2   p2

12

Solving this two-stage Stackelberg game-Nash bargaining problem, we can

13

obtain the optimal retail price p1o and p2o , the optimal ordering quantity q11o , q12o ,

14

o q1o and q2o , and the bargaining wholesale price w1 and w2o . On this basis, we can

15

get the optimal (or bargaining) profits of S1, M1, SC1, S2, M2, SC2, and the

16

corresponding social welfare of the exporting country market (market 1) and the

17

importing country market (market 2).

18

4.2 Trade Protection Scenario ( τ

> 0, ϕ = 1, κ > 0,η = 0 )

19

In the trade protection scenario, PV supply chain 1 will not implement any price

20

discrimination strategy for the PV module product exported to Country 2, i.e., ϕ

21

Its domestic retail price of PV module product equals to the foreign retail price.

22

However, Country 2 will impose tariff on the PV module product imported from 12

=1.

τ > 0.

1

Country 1 to protect its own industries, i.e.,

The decision sequence is as

2

follows: Firstly, the C-Si supplier S1 and the C-Si module manufacturer M1 in the

3

exporting country cooperate with each other via Nash bargaining mechanism, i.e., S1

4

and M1 bargain over the wholesale price of module to achieve cooperation within PV

5

supply chain 1 in the exporting Country 1, so does S2 and M2 within PV supply chain

6

2 in the importing Country 2; then, PV supply chain 1 sets the domestic and foreign

7

retail price of PV module product to maximize its profit, so does PV supply chain 2 in

8

the importing Country 2; finally, the price competition occurs in PV market of

9

Country 2. The Stackelberg game-Nash bargaining model for the dual competing PV

10

supply chains can be formulated as (Superscript t: trade protection scenario):

11

 max  Π w , p t , p t  λ Π w , p t , p t 1− λ  w1  S1 ( 1 1 2 )   M1 ( 1 1 2 )   t t t t t  s.t. Π S1 ( w1 , p1 , p2 ) + Π M1 ( w1 , p1 , p2 ) = Π SC1  1− λ λ  max  Π S2 ( w2 , p2t , p1t )  Π M 2 ( w2 , p2t , p1t )       w2  s.t. Π S ( w2 , p2t , p1t ) + Π M ( w2 , p2t , p1t ) = Π tSC 2 2 2  t t t t  p1 , p2 , Π SC and Π SC are derived from solving the following problem 1 2   max Π SC1 ( p1 , p2 )   p1  max Π SC ( p2 , p1 ) 2   p2

12

Solving this two-stage Stackelberg game-Nash bargaining problem, we can

13

obtain the optimal retail price p1t and p 2t , the optimal ordering quantity q11t , q12t ,

14

t q1t and q 2t , and the bargaining wholesale price w1 and w2t . On this basis, we can

15

get the optimal (or bargaining) profits of S1, M1, SC1, S2, M2, SC2, and the

16

corresponding social welfare of the exporting country market (market 1) and the

17

importing country market (market 2).

18

4.3 Price Discrimination Scenario ( τ

19

In the price discrimination scenario, PV supply chain 1 will implement the price

20

discrimination strategy, i.e., its domestic retail price of PV module product is set at

21 22

p1

= 0, 0 < ϕ < 1, κ = 0, η > 0 )

while its foreign retail price is set at ϕ p1 , 0 < ϕ < 1 . The importing Country 2

does not impose any tariff on imported PV module product to protect its own 13

τ = 0.

1

industries, i.e.,

2

S1 and the C-Si module manufacturer M1 in Country 1 cooperate with each other via

3

Nash bargaining mechanism, i.e., S1 and M1 bargain over the wholesale price of

4

module to achieve a cooperation within PV supply chain 1 in the exporting country, so

5

do S2 and M2 within PV supply chain 2 in the importing country; then, PV supply

6

chain 1 sets its domestic and foreign retail price of PV module product to maximize

7

its profit, so does PV supply chain 2; finally, the price competition occurs in the

8

importing Country 2’s PV market. The Stackelberg game-Nash bargaining model for

9

the dual competing PV supply chains can be formulated as (Superscript d: price

10

11

The decision sequence is as follows: Firstly, the C-Si supplier

discrimination scenario): 1− λ d d  max  Π w , p d , p d  λ  Π  w , p , p ( ) ( ) S 1 1 2 M 1 1 2   1   w1  1  d d d d d  s.t . Π S1 ( w1 , p1 , p2 ) + Π M 1 ( w1 , p1 , p2 ) = Π SC1  1− λ λ  max  Π S2 ( w2 , p 2d , p1d )   Π M 2 ( w2 , p 2d , p1d )       w2  s.t . Π S ( w2 , p 2d , p1d ) + Π M ( w2 , p 2d , p1d ) = Π dSC 2 2 2  d d d d  p1 , p 2 , Π SC and Π SC are derived from solving the following problem 1 2    max Π SC1 ( p1 , p 2 )   p1   max Π SC ( p 2 , p1 ) 2   p2

12

Solving this two-stage Stackelberg game-Nash bargaining problem, we can

13

obtain the optimal retail price p1d and p2d , the optimal ordering quantity q11d , q12d ,

14

d q1d and q 2d , and the bargaining wholesale price w1 and w2d . On this basis, we can

15

get the optimal (or bargaining) profits of S1, M1, SC1, S2, M2, SC2, and the

16

corresponding social welfare of the exporting country market (market 1) and the

17

importing country market (market 2).

18

4.4 Anti-Price Discrimination Scenario ( τ

19

In the anti-price discrimination scenario, PV supply chain 1 in the exporting

20

country will implement the price discrimination strategy, i.e., its domestic retail price

21

of PV module product is set at p1 while the foreign retail price is set at ϕ p1 ,

22

0 < ϕ < 1 ; but now the importing Country 2 will impose tariff on the imported PV 14

> 0, 0 < ϕ < 1, κ > 0, η > 0 )

1

module product from Country 1 to retaliate the unfair trade behavior of PV supply

2

chain 1 (Country 1), i.e.,

3

supplier S1 and the C-Si module manufacturer M1 in the exporting Country 1

4

cooperate with each other via Nash bargaining mechanism, i.e., S1 and M1 bargain

5

over the wholesale price of module to achieve a cooperation within PV supply chain 1

6

in Country 1, so do S2 and M2 within PV supply chain 2 in the importing Country 2;

7

then, PV supply chain 1 decides its domestic and foreign retail price of PV module

8

product to maximize its profit, so does PV supply chain 2 in the importing Country 2;

9

finally, the price competition occurs in the importing Country 2’s PV market. The

10

Stackelberg game-Nash bargaining model for the dual competing PV supply chains

11

can be formulated as (Superscript a: scenario with anti-price discrimination):

12

13

τ > 0.

The decision sequence is as follows: firstly, the C-Si

1− λ  max  Π w , p a , p a  λ  Π w , pa , pa   w1  S1 ( 1 1 2 )   M 1 ( 1 1 2 )   a a a a a  s.t . Π S1 ( w1 , p1 , p 2 ) + Π M 1 ( w1 , p1 , p 2 ) = Π SC1  1− λ λ  max  Π S 2 ( w2 , p 2a , p1a )   Π M 2 ( w2 , p 2a , p1a )       w2  s.t . Π S ( w2 , p 2a , p1a ) + Π M ( w2 , p 2a , p1a ) = Π aSC 2 2 2  a a a a  p1 , p 2 , Π SC and Π SC are derived from solving the following problem 1 2    max Π SC1 ( p1 , p 2 )   p1   max Π ( p , p ) SC 2 2 1    p2

Solving this two-stage Stackelberg game-Nash bargaining problem, we can and p2a , the optimal ordering quantity q11a , q12a ,

14

obtain the optimal retail price

15

q1a and q2a , and the bargaining wholesale price w1 and w2a . On this basis, we can

16

get the optimal (or bargaining) profits of S1, M1, SC1, S2, M2, SC2, and the

17

corresponding social welfare of the exporting country market (market 1) and the

18

importing country market (market 2).

p1a

a

19

15

Table 1 Analytical Results for Dual International Competing PV Supply Chain System Scenario

Free Trade (FT)

Var.& R.

p1*

* 2

p

p1o =

p2o =

2b  a1 + 2b ( c1 + c01 ) + bl  + d  a2 + b ( c2 + c02 ) 8b 2 − d 2 4b  a2 + b ( c2 + c02 )  + d  a1 + 2b ( c1 + c01 ) + bl  8b − d 2

2

Trade Protection (TP)

p1t =

p2t =

Price Discrimination (PD)

2b  a1 − τ a12 + 2b ( c1 + c01 ) + bl  + (1 − τ ) d  a2 + b ( c2 + c02 )  4 ( 2 − τ ) b 2 − (1 − τ ) d 2

2b ( 2 − τ )  a2 + b ( c2 + c02 )  + d  a1 − τ a12 + 2b ( c1 + c01 ) + bl  4 ( 2 − τ ) b − (1 − τ ) d 2

2

p1d =

p2d =

{

Anti-Price Discrimination (AD)

}

2b ( a11 + ϕ a12 ) + b ϕl + (1 + ϕ )( c1 + c01 )  + dϕ  a2 + b ( c2 + c02 ) 4 (1 + ϕ ) b − ϕ d 2

2

2

2

{

}

2 (1+ ϕ 2 ) b a2 + b ( c2 + c02 )  + ϕd ( a11 + ϕa12 ) + b ϕl + (1+ ϕ )( c1 + c01 )  4 (1+ ϕ ) b − ϕ d 2

2

2

2

{

}

p1a =

2b  a11 + (ϕ − τ ) a12  + b ϕl + (1 + ϕ )( c1 + c01 )  + d (ϕ − τ )  a2 + b ( c2 + c02 )  4 1 + ϕ (ϕ − τ ) b 2 − ϕ (ϕ − τ ) d 2

p2a =

2b 1+ ϕ (ϕ −τ )  a2 + b ( c2 + c02 )  + dϕ a11 + (ϕ −τ ) a12  + b ϕl + (1+ϕ )( c1 + c01 )  4 1+ ϕ (ϕ −τ )  b2 −ϕ (ϕ −τ ) d 2

{

* q11

q11o = a11 − bp1o

q11t = a11 − bp1t

q11d = a11 − bp1d

q11a = a11 − bp1a

* q12

q12o = a12 − bp1o + dp2o

q12t = a12 − bp1t + dp2t

q12d = a12 − bϕ p1d + dp2d

q1*

q1o = a1 − 2bp1o + dp2o

q1t = a1 − 2bp1t + dp2t

q1d = a1 − (1 + ϕ ) bp1d + dp2d

q12a = a12 − bϕ p1a + dp2a

q1a = a1 − b (1 + ϕ ) p1a + dp2a

q2*

q2o = a2 − bp2o + dp1o

q2t = a2 − bp2t + dp1t

q2d = a2 − bp2d + d ϕ p1d

q2a = a2 − bp2a + d ϕ p1a

 qo  1 qo  w1o = λ  1 + l  − 12o   + c1  2b  2 q1   λqo w2o = 2 + c2 b Π oS1 = λΠ oSC1

 qt  w1t = λ   p1t − ( c1 + c01 )  − ( l + τ p1t ) 12t  + c1 q1  

 qd  w1d = λ   p1d − ( c1 + c01 )  − (1 − ϕ ) p1d + l  12d  + c1 q1  

 qa  w1a = λ  p1a − ( c1 + c01 ) − (1 − ϕ + τ ) p1a + l  12a  + c1 q1  

w2t = λ  p2t − ( c2 + c02 )  + c2

w2d = λ  p2d − ( c2 + c02 ) + c2

w2a = λ  p2a − ( c2 + c02 )  + c2

Π tS1 = λΠ tSC1

Π dS1 = λΠ dSC1

Π aS1 = λΠ aSC1

w1* w2* Π *S1

Π oM1 = (1 − λ ) Π oSC1

Π *M1

Π oSC1 =

Π *SC1

1 o 2 1 o ( q1 ) + l  2 q1 − q12o  2b

Π tM1 = (1 − λ ) Π tSC1

Π dM1 = (1 − λ ) Π dSC1

Π aM1 = (1 − λ ) Π aSC1

Π tSC1 =  p1t − ( c1 + c01 )  q1t − ( l + τ p1t ) q12t

Π dSC1 =  p1d − ( c1 + c01 )  q1d − (1 − ϕ ) p1d + l  q12d

Π aSC1 =  p1a − ( c1 + c01 )  q1a − (1 − ϕ + τ ) p1a + l  q12a

Π *S2

Π oS2 = λΠ oSC2

Π tS2 = λΠ tSC2

Π dS2 = λΠ dSC2

Π aS2 = λΠ aSC2

Π *M 2

Π oM 2 = (1 − λ ) Π oSC2

Π tM 2 = (1 − λ ) Π tSC2

d Π dM 2 = (1 − λ ) Π SC 2

a Π aM 2 = (1 − λ ) Π SC 2

Π tSC2 =  p2t − ( c2 + c02 )  q2t

Π dSC2 =  p2d − ( c2 + c02 )  q2d

Π aSC2 =  p2a − ( c2 + c02 )  q2a

ΠoSC2 =

Π *SC2

1 o 2 ( q2 ) b

SW 1*

SW1o

SW 1t

S W 1d

S W1a

* 2

o 2

t 2

d 2

SW 2a

SW

SW

SW

SW

2 1 1  a11 − q11o − b ( c1 + c01 + l )  q1o + ( q11o ) + lq11o 2b b 1 1 1  o o o 2 o o o 2  o o o SW 2o = 2  ( ba12 + da 2 ) q12 + ( ba2 + da12 ) q 2  −  b ( q12 ) + 2 dq12 q 2 + b ( q 2 )   − ( a11 − q11 ) q12 − ( c2 + c02 ) q 2 b − d 2  2  b

SW1o =

+ 2 1 1 − 2τ t 2  τ 1  q11 ) +  l + a11  q11t − κ  ( q12o − q12t )  (1 − τ ) ( a11 − q11t ) − b ( c1 + c01 + l )  q1t + (   2  b 2b b   2 2 + 2 1 1 1 − 1  o τ   t t t t   ba12 + da 2 ) q12t + ( ba 2 + da12 ) q 2t  −  b ( q12t ) + 2 dq12t q 2t + b ( q 2t )   − − − + + − SW2t = 2 a q q c c q q q κ ( ) ( ) ( ) 11 11 12 2 02 2 12 12 2  (    2  2  b −d  b

SW1t =

Note

1 − 2 (1 − ϕ ) d 2  1 − ϕ + 2 1 ϕ ( a11 − q11d ) − b ( c1 + c01 + l )  q1d + ( q11 ) +  b a11 + l  q11d + 12 η ( q12d − q12o )   2b b 2 2  + 2 1 1 1 ϕ   ( ba12 + da 2 ) q12d + ϕ ( ba 2 + da12 ) q2d  −  b ( q12d ) + (1 + ϕ ) dq12d q 2d + ϕ b ( q 2d )   − ( a11 − q11d ) q12d − ( c2 + c02 ) q 2d − η  ( q12d − q12o )  SW2d = 2 2         2 2 ϕ (b − d )   b SW1d =

+ 2 + 2 1 − 2 (1 − ϕ + τ ) a 2  1 − ϕ + τ 1 1 1  q11 ) +  a11 + l  q11a + η  ( q12a − q12o )  − κ  ( q12o − q12a )  (ϕ − τ ) ( a11 − q11a ) − b ( c1 + c01 + l )  q1a + (    b 2b b 2  2    + 2 + 2 ϕ −τ 1 1 1 1  a a a a 2 a a a 2  a a  ( ba12 + da 2 ) q12 + ϕ ( ba 2 + da12 ) q2  − SW 2 = b ( q12 ) + (1 + ϕ ) dq12 q 2 + ϕ b ( q2 )   − a11 − q11 ) q12 − ( c2 + c02 ) q 2a − η  ( q12a − q12o )  + κ  ( q12o − q12a )  ( 2 2      2 b 2  2  ϕ (b − d ) 

SW1a =

Var.& R.: Variables & Results

16

}

1

5. Numerical and Sensitivity Analyses

2

A dual competing PV supply chain system based on the cost data from

3

EnergyTrend (Chueh, 2018) is designed for the numerical and sensitivity analyses of

4

the theoretical models developed in section 4. The parameter values for the numerical

5

analyses are summarized in Table 2.

6

Table 2 Parameter Values for Numerical and Sensitivity Analyses Parameters

a11

choke quantity of manufacturer 1’s demand function in domestic market

5.40E+09

a12

choke quantity of manufacturer 1’s demand function in foreign market

3.60E+09

a2

choke quantity of manufacturer 2’s demand function in domestic market

2.50E+09

b

The reaction extent of the demand w.r.t the change of retail price

1.00E+09

d

The reaction extent of the demand w.r.t the change of competitor’s retail price

1.00E+08

c1

The unit costs of C-Si materials for supplier 1

0.85 Yuan/Watt

c01

The unit processing costs of PV module products for manufacturer 1

0.22 Yuan/Watt

c2

The unit costs of C-Si materials for supplier 2

0.90 Yuan/Watt

c02

The unit processing costs of PV module products for manufacturer 2

0.23 Yuan/Watt

l

The unit logistics cost of PV module exported from country 1 to country 2

0.20 Yuan/Watt

ϕ

Price discrimination factor

90%

τ

Tariff rate

30%

λ

Supplier’s bargaining power

0.4

κ

The coefficient of trade-protection damage

1.00E-07

η

The coefficient of price-discrimination damage

1.00E-07

Note

7

value

1 Yuan=0.141 USD

Supplier 1’s unit cost of C-Si materials c1 is 0.85 Yuan/Watt and Supplier 2’s c 2

8

is 0.90 Yuan/Watt. Manufacturer 1’s unit processing cost of PV module products c01

9

is 0.22 Yuan/Watt and Manufacturer 2’s c02 is 0.23 Yuan/Watt. The unit logistics cost

10

of PV module products exported from Country 1 to Country 2 l is 0.20 Yuan/Watt.

11

The choke quantity of the demand function a11 , a12 and a 2 are 5.40E+09 Watt,

12

3.60E+09 Watt and 2.50E+09 Watt respectively. The reaction extent of the ordering

13

quantity (demand) w.r.t. the change of retail price

14

extent of the ordering quantity (demand) w.r.t. the change of competitor’s retail price

15

d is 1.00E+08. The price discrimination factor ϕ is set at 90%. The tariff rate τ is

16

30%. The supplier’s bargaining power λ is 40%. The coefficient of trade-protection 17

b

is 1.00E+09. The reaction

1

damage κ is 1.00E-07. The coefficient of price-discrimination damage η is

2

1.00E-07.

3

5.1 Numerical Analysis

4

The numerical analysis and its results for the four modeling scenarios developed

5

in section 4 will be reviewed and discussed in detail with the variable values and

6

performance results.

7

(1) Price

8

In Table 3, for all scenarios, the wholesale and retail prices in market 1 are much

9

higher than those in market 2 since market 2 has two competing supply chains while

10

market 1 has only one supply chain without competition. In the wholesale sector, due

11

to its cooperation game design, there are little differences of the wholesale prices

12

across four modeling scenarios in either market 1 or market 2. In the retail sector, the

13

competitive market (market 2) is also indifferent regarding the retail prices of four

14

scenarios; however, the market without competition (market 1) shows a lower retail

15

price set at free trade (FT) scenario while the other three non-free trade scenarios are

16

setting much higher retail prices with anti-price discrimination (AD) scenario at the

17

highest level.

18 19

Table 3 Numerical Results of Dual International Competing PV Supply Chain Models (Price Analysis) Free Trade (FT)

Trade Protection (TP)

Price Discrimination (PD)

Anti-price Discrimination (AD)

w1*

1.55

1.54

1.58

1.53

* 2

1.23

1.24

1.23

1.23

* 1

2.88

3.06

3.05

3.21

* 2

1.96

1.97

1.95

1.96

Scenario Variable/Result

w p p

20

The key findings can be synthesized as: “Under a one-sided dual supply chain

21

trade, the retail prices will be determined by the market force rather than the price

22

discrimination of business or trade protection of government in the competitive

23

market; however, in the non-competitive market, the situation will be reversed, that is,

24

the retail prices will be affected and biased toward a higher level due to the price

25

discrimination or trade protection actions.” A proposition can be made for this 18

1

analysis result: the supply chain 1 must raise its home market retail price to offset the

2

increased costs either by the trade protection or price discrimination in the foreign

3

market.

4

(2) Quantity (Demand)

5

In Table 4, market 1 is supplied by a single supply chain with no competition.

6

Table 4 shows the highest demand can be created under FT scenario. If either TP or

7

PD scenario is the case, the demand will be reduced due to the offset effect of a higher

8

retail price (see Table 3); and the demand will be reduced even more when both TP

9

and PD are enacted into an AD scenario.

10 11

Table 4 Numerical Results of Dual International Competing PV Supply Chain Models (Quantity Analysis) Scenario Variable/Result

Free Trade (FT)

Trade Protection (TP)

Price Discrimination (PD)

Anti-price Discrimination (AD)

q11*

2,516,020,025

2,341,837,185

2,353,400,904

2,188,775,875

* 12

911,939,925

738,627,999

1,053,270,510

905,848,796

* 1

3,427,959,950

3,080,465,185

3,406,671,414

3,094,624,671

829,198,999

837,908,141

822,096,959

829,505,086

4,257,158,949

3,918,373,326

4,228,768,373

3,924,129,757

q

q

* 2

q

q +q * 1

* 2

12

Market 2 is supplied by two competing supply chains with supply chain 1 as the

13

foreign competitor and supply chain 2 as the domestic competitor. Trade protection by

14

government 2 will result in a higher demand for supply chain 2 but lower demand for

15

supply chain 1; nevertheless, the total demands on two markets are not higher than

16

that under FT (free trade). If only price discrimination strategy is exerted by supply

17

chain 1, a clear increase of its demand and a clear drop of supply chain 2 in market 2

18

can be seen; the total demands are higher than that under TP but still lower than that

19

under FT. If both TP and PD, i.e., AD, are exercised, the demands of two supply

20

chains will be between those of TP and PD; the total demands are also in-between

21

those of TP and PD.

22

The key finding can be summarized as: “Free Trade scenario can create the

23

highest total demand of two markets comparing to the other three non-free trade

24

modeling scenarios. This result implies that free trade can create the most total

25

demands for retail consumption while all other trade-biased policies will cause a 19

1

reduction of the total demands with TP (trade protection) causing the most serious

2

drop in consumption.” A proposition can be made for this analysis result: Free trade

3

without any public or business interference on the market with competition will create

4

the highest total consumption demands for the dual international competing supply

5

chains.

6

(3) Profit & Social Welfare

7

In Table 5, a one-sided trade protection by Government 2 (TP) will create the

8

highest profit for supply chain 2 and the highest social welfare for Country 2 but

9

cause the second lowest profit for supply chain 1 and the lowest social welfare for

10

Country 1. This situation may easily trigger supply chain 1 to react by adopting a

11

price discrimination strategy to mitigate the trade protection impact. However, the

12

strategy actually does not help to increase the profit for supply chain 1 and it hurts the

13

profit of supply chain 2 even harder. Regarding social welfare, under trade protection

14

status, a subsequent price discrimination strategy by supply chain 2 will increase

15

substantially the social welfare of Country 1 by sacrificing a lot of the social welfare

16

of Country 2.

17 18

Table 5 Numerical Results of Dual International Competing PV Supply Chain Models (Profit & Social Welfare Analysis) Scenario Variable/Result

Free Trade (FT)

Trade Protection (TP)

Price Discrimination (PD)

Anti-price Discrimination (AD)

Π *S1

2,414,345,088

2,119,634,931

2,480,832,094

2,112,624,737

Π

* M1

3,621,517,632

3,179,452,397

3,721,248,142

3,168,937,105

Π

* SC1

6,035,862,719

5,299,087,328

6,202,080,236

5,281,561,841

* S2

275,028,392

280,836,021

270,337,364

275,231,475

Π

* M2

412,542,588

421,254,031

405,506,046

412,847,212

Π

* SC 2

687,570,980

702,090,052

675,843,410

688,078,687

SW1*

9,201,041,102

6,539,336,853

9,970,044,856

7,675,076,664

* 2

1,531,228,222

3,574,242,035

1,054,220,839

2,741,590,457

Π

SW

19

A one-sided price discrimination strategy by supply chain 1 will create the

20

highest profit for supply chain 1 but cause the lowest profit to supply chain 2. It is true

21

also for the social welfare values. This situation will very likely trigger the retaliation

22

of Country 2 under the request of supply chain 2 to protect domestic industry by

23

raising up the import tariff and lead AD scenario in which case supply chain 1 and 20

1

Country 1 will suffer from large drop in both profit and social welfare while supply

2

chain 2 and Country 2 will gain back some grounds regarding the profit and social

3

welfare.

4

Since either TP or PD action will lead to AD route and can be deemed as

5

unstable scenarios, FT may be the most sustainable scenario to be maintained for both

6

supply chains and their governments.

7

The key finding can be summarized as: “Any one-sided non-free trade action

8

will receive a higher supply chain profit and social welfare but create an unstable

9

trade system that will eventually lead to the counter action of the suffered supply

10

chain or country.” A proposition can be made for this analysis result: The stability of a

11

dual international competing supply chain system depends on whether the trade

12

policy is a free trade or non-free trade one. A free trade policy makes the trade system

13

more stable while a non-free trade policy makes the trade system unstable.

14

(4) Overall

15

Table 6 provides an overall analysis. FT is the best scenario for total demand

16

creation while TP is the worst; PD is the best scenario for total supply chain profit

17

generation while AD is the worst; PD is also the best scenario for total social welfare

18

output while TP is the worst. FT is actually the second-best scenario regarding total

19

supply chain profit generation and total social welfare output. Since TP and PD

20

scenarios will eventually lead to AD and create an unstable trade system, FT may be

21

the best state to maintain for both supply chains and governments.

22 23

Table 6 Numerical Results of Dual International Competing PV Supply Chain Models (Overall Analysis) Scenario Variable/Result

q1* + q2*

Π *SC1 + Π *SC2 * 1

* 2

SW +SW

Free Trade (FT)

Trade Protection (TP)

Price Discrimination (PD)

Anti-price Discrimination (AD)

4,257,158,949

3,918,373,326

4,228,768,373

3,924,129,757

6,723,433,699

6,001,177,380

6,877,923,646

5,969,640,528

10,732,269,324

10,113,578,888

11,024,265,695

10,416,667,121

24 25 26

5.2 Sensitivity Analysis Since the research focus is on the impact of free and non-free trade policies, the 21

1

sensitivity analysis will investigate how the changes of two key non-free trade

2

parameters - price discrimination factor ( ϕ ) and tariff rate ( τ ) - affect the profit and

3

social welfare levels in two markets under four modeling scenarios. The incremental

4

scale and range of the change of each parameter are listed in Table 7. It is noted that

5

the price discrimination factor reflects the intensity of the price discrimination: the

6

lower the factor value is, the stronger the discrimination effect, i.e. unfair trade

7

practice of PV supply chain 1 against PV supply chain 2 in market 2, will be. Similar

8

but inversely, the tariff rate reflects the level of trade protectionism: the higher the rate

9

is, the stronger the protection effect, i.e., unfair trade regulation of Country 2 against

10

PV supply chain 1, will be. Also note that when the price discrimination factor equals

11

to 100%, there will be no price discrimination and is equivalent to FT (free trade)

12

scenario; and when the tariff rate equals to 0%, there will be no tariff exercised and is

13

also equivalent to FT scenario. The sensitivity analysis results for each parameter will

14

be presented and discussed below.

15

Table 7 Range of Key Parameter for Sensitivity Analysis Parameter

Original Value

± Increment

Range

ϕ

Price discrimination factor

90%

1%

[10%, 100%]

τ

Tariff rate

30%

1%

[0, 90%]

16 17

5.2.1 Price Discrimination Factor ( ϕ )

18

In Figure 2, two scenarios, FT and TP, are not affected by price discrimination

19

factor ( ϕ ) changes so that constant profits and social welfares can be observed. There

20

is little difference of social welfares in two markets but larger gaps for supply chain

21

profits. In other words, no matter how supply chain 1 discriminates on the PV module

22

retail price against market 2, the trade protection policy, if exercised by Country 2,

23

will cause the reduction of supply chain 1’s profit and the increase of supply chain 2’s

24

profit at a fixed amount but bring not much change to the social welfares in two

25

countries. 22

1

2

PV Supply Chain 1 Profit

Country 1 Social Welfare

PV Supply Chain 2 Profit

Country 2 Social Welfare

Figure 2 Price discrimination factor ( ϕ ) Change Impact

3

Since most countries in the world are already members of the World Trade

4

Organization (WTO), it is less likely that a country will unilaterally impose undue

5

tariffs on the imported products. A trade conflict or trade war typically gets started

6

when a supply chain of an export country practices a price discrimination strategy to

7

increase the market share in its foreign market of an imported country. Thus, the most

8

likely routes for a trade conflict are illustrated by four arrow paths in the four

9

diagrams in Figure 2. Each rout of a diagram always starts with a free trade status (FT

10

scenario) from the circle dot and then goes through the price discrimination stage

11

triggered by supply chain 1 (PD scenario), tariff retaliation stage countered by

12

Country 2 (AD scenario), eventually returning to the free trade status (FT scenario).

13

As it is shown in the four diagrams in Figure 2, when supply chain 1 deviates from FT

14

status by taking the price discrimination strategy, Country 2 will retaliate by imposing

15

a tariff when the price discrimination gets to an intolerable level. If supply chain 1

16

continues the path to discriminate further on the retail price, its profit will drop even 23

1

more to the level until it gives up its price discrimination practice. The trade conflict

2

will then be resolved and the trade status will return back to the stable state of free

3

trade.

4

Regarding supply chain profits, the trade conflict gets more serious when

5

Country 2 starts retaliating by imposing tariff, supply chain 1’s profit will drop

6

dramatically and drop even further if it intends to conduct more intense price

7

discrimination. Supply chain 2’s profit will increase to a slightly higher level but drop

8

again when the price discrimination gets more intense. Only until supply chain 1 gives

9

up its price discrimination act, the supply chain profits of both supply chain can

10 11

recover and increase to their free trade profit levels. As far as the social welfares, it clearly exists a trade-off relationship. When the

12

trade conflict gets more intense due to the increasing retail price discrimination by

13

supply chain 1 in market 2, the social welfare in Country 1 will increase while the

14

social welfare in Country 2 will decrease at a similar rate but at opposite directions.

15

5.2.2 Tariff Rate ( τ )

16

In Figure 3, two scenarios, FT and PD, are not affected by tariff rate ( τ ) changes

17

so that constant profits and social welfares can be observed. Once PD is enacted by

18

supply chain 1 and the trade system deviates from free trade (FT) status, no matter

19

how large the tariff Country 2 imposes on the imported PV module product, supply

20

chain 1’s profit will be increased but supply chain 2’s profit will be reduced by a fixed

21

amount and a similar trend can be seen for the social welfares but at a relatively

22

smaller change scale. In other words, under tariff rate changes, supply chain 1’s PD

23

strategy will bring up its profit and Country 1’s social welfare by a constant amount

24

but reversely for supply chain 2’s profit and Country 2’s social welfare.

25

The circle dot in Figure 3 indicates the starting status of trade: a free trade (FT).

26

The dynamics in the trade system changes when supply chain 1 moves to the price

27

discrimination stage and tries to gain more profit and market share in market 2. When

28

Country 2 retaliates by imposing a tariff rate of 0.3 i.e., the trade system entering into

29

an AD stage, supply chain 1’s profit drops to a much lower level than that of FT stage

30

while supply chain 2’s profit is recovered back to FT stage. However, the social 24

1

welfare in Country 1 will be reduced to a lower level than that of FT stage but the

2

social welfare in Country 2 will be increased to a higher level than that of FT stage.

3

When Country 2 intensifies the retaliation by keep raising up the tariff, supply chain

4

1’s profit will continue to drop at a much higher rate than the drop rate of the social

5

welfare in Country 1 with a similar but reverse trend (increasing rather than dropping

6

rate) for supply chain 2’s profit and Country 2’s social welfare. Supply chain 1 will

7

stop its price discrimination act when it can no longer stand the dropping of profit due

8

to the increased tariff rate by Country 2. The trade system will then return to the stable

9

state of free trade (FT).

10

11

PV Supply Chain 1 Profit

Country 1 Social Welfare

PV Supply Chain 2 Profit

Country 2 Social Welfare

Figure 3 Tariff Rate ( τ ) Change Impact

12 13 14 15 16

6. Managerial Insights and Policy Implications This study provides two insightful theoretical findings that may be valuable to the PV industry practitioners and policy makers. The price discrimination factor analysis in section 5.2.1 can be derived into the 25

1

following proposition: In a dual international competing supply chain system, when

2

the price discrimination of an export supply chain gets more intense, it will hurt both

3

the export supply chain and local competing supply chain regarding their supply

4

chain profits; meanwhile, the export country will gain more social welfare due to the

5

sacrifice of the social welfare of the import country causing the retaliation by the

6

import country. In other words, the price discrimination practice will create an

7

unstable international competing trade system with dual supply chains and hurt more

8

on the price discrimination exercising supply chain. Thus, from a PV supply chain

9

perspective, it is not wise to adopt a price discrimination strategy to pursue more

10

profits in its foreign market.

11

The tariff rate analysis in section 5.2.2 can be gleaned into the following

12

proposition: In a dual international competing supply chain system, the deviation of

13

the export supply chain from a free trade status by exercising price discrimination

14

strategy to gain more profit and market share will eventually result in the retaliation

15

of the import country by imposing tariff gradually until the export supply chain stops

16

the price discrimination practice. The price discrimination strategy and action by the

17

export supply chain will hurt, rather than, gain in terms of supply chain profit and

18

country social welfare values. The local supply chain will gain more profit and the

19

import country will increase more social welfare by taking retaliation policy to impose

20

tariff on the imported products. However, the price of trade conflict and war is an

21

unstable and unsustainable trade system that hurts both supply chains and countries.

22

Thus, from a government’s perspective, when a price discrimination practice is found

23

from a foreign export supply chain, it must certainly impose tariff to protect its

24

domestic supply chain profit and social welfare from being eroding.

25

The foresight of the theoretical findings imply that a wiser decision for the

26

export supply chain with the prowess to discriminate on the retail price of the import

27

market (due to, perhaps, subsidy by the export country) is not to utilize a price

28

discrimination strategy at the onset since only a stable rather than unstable trade

29

system can bring sustainable business and social values to the participating supply

30

chains and countries. The foresight should be applicable to the possible impact of 26

1

other markets on the supply chains in the solar industry with similar trading

2

conditions.

3

The sensitivity analysis casts an insight that any unfair trade policy will benefit

4

only the country who exercises the unfair trade policy that eventually leads to

5

escalating trade conflict and brings economic damages to the trading stakeholders.

6

However, the damages to the world trade and the involved parties may be substantial

7

and need to be absorbed by all trading stakeholders that may linger around for many

8

years to come before the economies of the trade conflict countries recover back to

9

their original free trade states.

10

Examining the most notable trade war example between U.S. and China, China

11

has been subsidizing its solar panel industry for years and indeed helps China’s solar

12

panel industry to become the powerhouse of solar panel export trade while U.S. as

13

one of the global large promoters of renewable energy has been importing from China

14

and other exporting countries many solar panels causing the local solar industry to

15

lobbying U.S. government against the solar panel import by levying anti-dumping

16

duties, China solar panel import in particular. Since the anti-price discrimination

17

(anti-dumping) scenario will cause more overall economic damages with the reduced

18

demands, could the policy makers come up with a wiser approach at the stage of trade

19

protection to prevent the trade conflict from escalating to the most serious

20

anti-dumping situation and worsen the total economic demands of the solar panels?

21

At this critical time of the growing impact of climate change on earth, any means

22

that can economically create and satisfy more solar energy demands should deserve

23

more intention and resource to facilitate its implementation. What might be more

24

critical to ask now is: “Is there a better way to solve the trade conflict problem before

25

it gets escalated from a trade protection scenario (TP) to the most serious

26

anti-dumping scenario (AD)?” There seems to have no clear and easy answer to the

27

above question yet.

28

The on-going bi-lateral trade negotiation between U.S. and China since President

29

Xi of China (PRC) visited Trump’s Mar-a-Lago estate in Florida during April 6-7,

30

2017, where they agreed to set up a 100 Day Action Plan to resolve trade differences 27

1

(Wong and Koty, 2019), has indicated that such negotiation is brutal and brought to

2

both parties and also the world trade community many uncertainties and unpleasant

3

experiences, even though it may eventually produce something new and innovative

4

ways for resolving large trade disputes between trading parties (which may be too late

5

and too minimal for the damages already created).

6

If the governments and PV supply chains of two solar product trade conflicting

7

countries can view from the angle of facilitators of the solar energy consumption for

8

reducing climate change impact, there might be much better approach(es) than the

9

conventional retaliation approach that would escalate the trade conflict to the level of

10

a trade war. For the private sector, for example, since supply chain 1 may have both

11

the cost and marketing advantages over supply chain 2, could supply chain 1 take the

12

initiative to establish a collaborative, rather than a competing relationship with supply

13

chain 2 to serve market 2 together without playing a typical free market competition

14

game? Regarding the public sector, could both governments be more rational and

15

work out together (collaboratively, rather than confronting with each other) a joint

16

solar energy industry development policy that taps into the strength of the solar

17

energy industries in both countries to create more demands and values for the solar

18

energy consumers in market 2? These are some possible alternative solutions

19

deserving more researches to explore in the future to resolve the problems caused by

20

the existing trade conflict escalating approach. However, they are also very

21

challenging research issues to investigate.

22 23

7. Conclusion

24

This study has explored a contemporary trade conflict issue heated up by the

25

trade war between two largest economies in the world. Since the solar industry is a

26

fast developing and critical renewable energy industry sector with many global

27

suppliers competing fiercely in the world market, a dual international competing PV

28

module supply chain system is conceptualized to conduct a game-theoretical

29

modeling study for the exploration. Four modeling scenarios including Free Trade 28

1

(FT), Trade Protection (TP), Price Discrimination (PD) and Anti-price Discrimination

2

(AD) are investigated. A real world–based dual international competing PV supply

3

chain system is designed for the numerical and sensitivity analyses. Two key findings

4

from the study can be summarized below:

5

Price discrimination strategy can create the most total supply chain profits

6

and social welfares for dual international competing PV supply chains but

7

this strategy will eventually lead to Trade Protection of the importing

8

country and erode the supply chain profits and social welfares.

9

Trade protection policy delivers the lowest total demands and social welfares

10

for the dual international competing PV supply chains.

11

The above findings imply that in the dual international competing PV supply

12

chains, Free Trade policy, rather than the other non-free trade policies, with its

13

capability to create more total market demand, provide higher total supply chain

14

profits, deliver better total social welfares, thus, maintain a stable trade system, would

15

be the most appropriate trade policy to take by both governments and supply chains

16

for the development of a sustainable solar energy sector.

17

However, human systems are imperfect. The key finding also echoes the recent

18

turbulence development of the world trade conflict that any unfair trade policy will

19

benefit only the country who exercises the unfair trade policy that eventually leads to

20

escalating trade conflict and brings economic damages to the trading stakeholders.

21

The damages to the world trade and the involved parties may be substantial and need

22

to be absorbed by all trading stakeholders that may linger around for many years to

23

come. Thus, an even more critical issue to explore is to find ways to resolve trade

24

conflict at the early stage of trade conflict, such as the trade protecting stage, before

25

the conflict is worsening to the most serious conflict stage and cause serious economic

26

and political damages to the involved parties and the world.

27

This study explores the trade conflict issue only through the lens of dual

28

international competing PV supply chains and game-theoretical approaches. With the

29

theoretical foundation laid down by this study, there are many more relevant and

30

critical issues that should be investigated in the future such as: possible trade 29

1

resolution approaches at the trade protection stage, dual international competing

2

supply chains in other important trading products, multiple international competing

3

PV supply chains, expanding the upstream C-Si materials purchasing and PV module

4

manufacturing to downstream PV system assembling and solar power energy

5

generation in the context of international competition, sensitivity analysis on other

6

relevant parameters such as unit cost of materials and processing, subsidy factor,

7

supplier bargaining power, et al. and empirical rather than theoretical focused studies.

8 9 10

Conflict of Interest Statement The authors declared that they have no conflicts of interest to this work.

11 12

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Highlights Trade conflicts for the dual international competing PV supply chains are depicted. Game-theoretical decision models under four scenarios are developed and compared. Trade policies for the dual international competing PV supply chains are explored. Free trade is the most appropriate trade policy for the governments and industries.

Declaration of Interest Statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.