Appendix A. Proofs of Propositions, Corollary, and Theorems
Table A1.
Summary of notations.
Table A1.
Summary of notations.
Symbol | Definition |
---|
, | The market bases for high market and low market, respectively |
| Manufacturing cost efficiency of the IR |
| Consumers’ willingness to pay for the remanufactured product |
s | Quality level of the product |
, | Prices made by the OEM and IR, respectively |
k | Scaling parameter |
, | Profit functions of the OEM and IR, respectively |
, | Demand functions of the OEM and IR, respectively |
Proof of Benchmark Case. In the benchmark case, we first study the full information case where both parties know the actual market size at the beginning of the selling season. The price and profit functions for the OEM and IR are listed here:
We first solve for
,
:
Here, to ensure that
is positive,
should be less than
. In addition, according to Assumption 3,
. In other words,
. Here, we have
, which leads to
. By combining these constraints of
, we can list the values of
:
We refer to as Case 1, to as Case 2, and to as Case 3.
In Case 1, where , then, we have .
In Case 2, where , hence, .
In Case 3, where , ; here, . We consider the solution of equilibrium by applying the Karush–Kuhn–Tucker (KKT) conditions.
In
Case 3,
,
When
,
, we have
Since we need to ensure that
, we include Equation (
A3) in this inequality, and we obtain
.
When , we have , and . Here, .
After solving the equation above, we conclude as shown below.
When
, we refer to it as Case 3-A:
When
, we refer to it as Case 3-B:
Here, .
We move on to Case 2, where .
.
Here, .
To summarize this case, we conclude as shown below.
When
, we refer to it as Case 2-A:
When
, we refer to it as Case 2-B:
Then, we move on to Case 1, where .
.
.
After solving the equilibrium, we can summarize the OEM’s decisions as shown below.
When
, we refer to it as Case 1-A:
When
, we refer to it as Case 1-B1:
When
, we refer it to as Case 1-B2:
After studying the three cases, we conclude that there are four thresholds for : , , , and . We study all conditions in the three cases as follows (the summary results can also be found in Proposition 1):
When , the following apply:
- –
When , cost efficiency is high. The dominant strategy is Case 3-A, where the IR produces the same amount as the OEM: , .
- –
When , cost efficiency is low, but , the customers’ preference for the IR’s product, is high, so the dominant strategy is Case 2-A, where the IR produces her optimal amount: , .
When , the following apply:
- –
When , the dominant strategy is Case 3-A, where the IR produces the same amount as the OEM: , .
- –
When , the dominant strategy is Case 2-A, where the IR produces her optimal amount: , .
- –
When , the dominant strategy is Case 2-B, where the IR’s optimal amount is 0: , .
When , the following apply:
- –
When , the dominant strategy is Case 3-A, where the IR produces the same amount as the OEM: , .
- –
When , the dominant strategy is Case 2-A, where the IR produces her optimal amount: , .
- –
When , the dominant strategy is Case 2-B, where the IR’s optimal amount is 0: , .
- –
When , the dominant strategy is Case 2-A, where the IR produces a 0 amount: , .
Next, we move on to the no information case, where neither the OEM nor the CM has information about the actual market size at the beginning of the selling season. When there is no information, we consider the market size () random ex ante, and it can be either high with probability p or low with probability .
The expected market size (
) is given as
. Hence, the expected profits for the OEM and the CM are as follows:
Here, we solve for . .
The first-order condition is
We can simplify the equation above as . Therefore, . Similar to the case with full information, we have three cases for the IR’s decisions: Case 1, where the IR produces 0; Case 2, where the IR produces an optimal amount; and Case 3, where the IR produces the same amount as the OEM. The analysis for the no information case follows the same steps as that for the full information case. Below, we summarize the equilibrium for the no information case:
When , the following apply:
- –
When , cost efficiency is high. The dominant strategy is Case 3-A, where the IR produces the same amount as the OEM: , .
- –
When , cost efficiency is low, but , the customers’ preference for the IR’s product, is high, so the dominant strategy is Case 2-A, where the IR produces her optimal amount.: , .
When , the following apply:
- –
When , the dominant strategy is Case 3-A, where the IR produces the same amount as the OEM: , .
- –
When , the dominant strategy is Case 2-A, where the IR produces her optimal amount: , .
- –
When , the dominant strategy is Case 2-B, where the IR’s optimal amount is 0: , .
When , the following apply:
- –
When , the dominant strategy is Case 3-A, where the IR produces the same amount as the OEM: , .
- –
When , the dominant strategy is Case 2-A, where the IR produces her optimal amount: , .
- –
When , the dominant strategy is Case 2-B, where the IR’s optimal amount is 0: , .
- –
When , the dominant strategy is Case 2-A, where the IR produces a 0 amount: , .
□
Proof of Asymmetric Case. We move on to
Section 4.3 and study the case where information is asymmetric.
In the separating equilibrium model, the OEM uses quantity as a signal of market size for the IR.
The OEM’s and IR’s price functions for the new and remanufactured products are
From Equation (A17), the IR’s belief regarding the market size is and depends on the OEM’s selling quantity (), and the market size signal quantity made known to the IR is denoted by . If , the IR deems the market size () to be high, i.e., . On the other hand, if , the IR deems the market size to be low, i.e., .
When the market size is high and the OEM tells the truth about the market size, we refer to this equation as Case HH. Then, we have
can take three values:
The results and profit stay the same as in the base model, the full information case.
When the OEM sends fake signals regarding the market size, that is, when the market size is high but the OEM prefers the IR to believe it is low, we refer to it as Case HL. Then, we have
In Case HL,
can take three values:
Accordingly, when , , then .
When , then . The profit function is
.
When , , the profit function is .
Figure A1 summarizes each case. When
or
, the IR’s decision is fixed and is not affected by the OEM’s decision.
Figure A1.
Competition in remanufacturing: profits in different cases.
Figure A1.
Competition in remanufacturing: profits in different cases.
We denote as , as , as , and as .
There exists a Perfect Bayesian Separating Equilibrium (PBSE) if and only if the OEM’s strategy of quantity (
) satisfies
Inequality (
A21) means that the OEM pretending to be a low type when the market is high hurts his own profits. Inequality (A22) means that the OEM pretending to be a high type when the market is low also hurts him. The last inequality guarantees that the production quantity of the IR is non-negative.
We now look at each HL scenario in Case HH.
The below applies to the case where and .
When and , we learn from the main model that . In Case HL, when , ; hence, the IR’s decision is fixed.
When , .
.
.
Here, we have four different combinations for the values of
and
:
To ensure that and , we need , and we have .
First, we need to check that . After expanding this equation, we obtain . This equation is satisfied, since . Therefore, .
Second, we need to ensure that . This condition is satisfied if .
If
, then
, but
,
. We have
Using the equations above, we have
. By solving this equality, we obtain
where
.
Next, we examine each scenario.
When
, it is also obvious that
. First, let us see that when
, the profits in Cases HH and HL are shown below in
Figure A2.
Figure A2.
Competition in remanufacturing: HH and HL profits when .
Figure A2.
Competition in remanufacturing: HH and HL profits when .
Here, the OEM chooses to reveal his information when . . Here, .
Then, let us examine
. The profits in Cases HH and HL are shown below in
Figure A3. Similarly, when the market size is high, it is optimal for the OEM to set the first–best-order quantity as
. In this scenario, the OEM chooses to reveal true information when
.
Figure A3.
Competition in remanufacturing: HH and HL profits when .
Figure A3.
Competition in remanufacturing: HH and HL profits when .
In the low-market case, the profits can be viewed as shown below in
Figure A4.
Figure A4.
Competition in remanufacturing: LL and LH profits.
Figure A4.
Competition in remanufacturing: LL and LH profits.
The below applies to the case where and .
When
and
, we learn from the main model that
. For the HH market, we still have two cases, depending on
and
, and accordingly, the profits can be viewed as shown below in
Figure A5.
Figure A5.
Competition in remanufacturing: HH and HL profits.
Figure A5.
Competition in remanufacturing: HH and HL profits.
In the case where , we have . Here, the OEM uses to indicate that the market is high. , and . The quantity that ensures that is satisfied is used as the upper bound for .
In the case where , , since when .
Then, let us move on and check the case where the market size is low. The profits are summarized in
Figure A6.
Figure A6.
Competition in remanufacturing: LL and HL profits when .
Figure A6.
Competition in remanufacturing: LL and HL profits when .
. when . is used when . , is used when the following equality is satisfied: . If from the HH market is less than , the OEM has incentive to deviate from telling the truth.
Another case we need to consider is when
.
Figure A7 shows the profits for Cases LL and LH.
Figure A7.
Competition in remanufacturing: LL and HL profits when .
Figure A7.
Competition in remanufacturing: LL and HL profits when .
Here, when , the market is low; otherwise, the market is high. Here, we also need to ensure that . Here, the constraint is satisfied if and if .
Figure A8 summarizes both the high- and low-market cases.
Figure A8.
Competition in remanufacturing: profits when and .
Figure A8.
Competition in remanufacturing: profits when and .
When the market is low, when . When and the market is low, the OEM does not have incentives to reveal true information, since pretending to have a high market makes the OEM be better off, but the best option for the OEM is to choose . When the market is high, . But to ensure that the OEM does not deviate, we need to ensure that ; otherwise, there is no separating equilibrium in this scenario. Hence, .
In other cases, where and , the proofs are very similar to the case for . When , we can easily obtain the most profitable quantity when the market size is low as ; therefore, . Hence, we will not list all of them here. The results are summarized below.
When and , . When , .
When and , . When , . When , .
When and , . When , . When , . When , .
When the market is high, the OEM’s decisions are those obtained from the benchmark model, where the OEM and the IR have equal information. Profits are the same for the symmetric and asymmetric information cases, and the OEM does not benefit from having an information advantage.
When the market size is low, under certain market circumstances, the OEM’s profits are the same for the symmetric and asymmetric cases. Under other circumstances, the OEM’s profit is lower in the asymmetric information case than in the symmetric case. Hence, we focus on the case where the OEM’s profit is lower.
We notice that when the market size is low, , and , we need to ensure that Inequality (A22) is satisfied. When the IR’s inference on the market size () is less than , the OEM’s decision stays the same as in the benchmark case; otherwise, the OEM chooses a lower quantity to produce, and the IR produces 0. □
Proof of Proposition 3. Full information vs. no information: We use the results from Proposition 1 and
Table 1. In Region A, when information is unknown,
;
; and
. We have
. When information is known,
;
; and
. We have
. Then, we have
. Hence, the absence of information leads to a profit drop for the OEM.
In Region D, in case of full information, , and . .
In case of no information, , and . .
. Hence, the OEM has more benefits in the full information case.
For the other two regions, the proof is very straightforward, and the results are similar, i.e., the OEM’s profit is higher in the full information scenario.
We further compare the quantities and qualities of the OEM and the CM between the no information and full information cases. We notice that given the structural similarities between the full information and no information cases, the only difference is the market size. In the case of no information, the market size is denoted by , whereas the full information case involves considering the expected value arising from high and low markets. Comparing the quantity and quality differences between the full information and no information cases, the equilibrium values in the full information case are always higher than those in the no information case.
Full information vs. asymmetric information: According to Proposition 2 and
Figure 2, when the market size is large, the OEM and IR have the same quantities as those obtained from the benchmark model when information is known to both parties. However, when the market size is small, the OEM’s behavior is different.
As shown in Region C in
Figure 2, specifically, the OEM signals the market size with
, leading to
. In this case, it is observed from
Figure A8 that
. Note that
is the quantity that satisfies the inequality in constraint (
13) and
is the quantity that satisfies the inequality in constraint (14). Consequently, the profit in the full information scenario with
and
surpasses that in the asymmetric information case with
and
. □