In supply chain finance, several scholars have conducted extensive research on the financing modes of external bank financing and internal trade credit financing. For examples, Kouvelis and Zhao (2011) explored the newsvendor problem in a supply chain with capital constraints and obtained the optimal price-only contract under bank financing in the presence of bankruptcy costs. Yan and Sun (2013) discussed that the commercial bank, as the leader, sets the appropriate loan amount according to the credit and collateral of the retailer. Feng et al. (2014) found that when a capital-constrained buyer obtains funds from a bank, the buyer’s profit and optimal purchase decision increase with bank financing. Huang et al. (2019) examined that a capital-constrained retailer obtains a short-term financing from a bank by supplier credit guarantee loan. In terms of internal trade credit financing, Xiao et al. (2016) discussed whether three kinds of trade credit contracts, namely revenue-sharing, buyback, and all-unit quantity discount, can realize the coordination of the capital-constrained supply chain. Gupta and Chen (2019) researched that small businesses with capital constraints can sell products to retailers through a consignment contract, and analyzed the condition that the retailer’s willingness to lend and the supplier’s willingness to accept. Yang et al. (2019) used a game model to consider the interactions among a retailer, an incumbent manufacturer and a capital-constrained new entrant manufacturer. Zhang et al. (2021) formulated the Stackelberg game models under centralized decision and decentralized decision to probe the pricing decision of a retailer-dominant dual-channel supply chain with manufacturer’s capital constraints. In addition, there are some studies on the hybrid financing of external bank financing and internal trade credit financing. For instances, Li et al. (2019) considered the optimal financing decisions for a capital-constrained manufacturer in a dual-channel supply chain. The manufacturer can choose three financing modes, namely, trade credit, bank loan, and hybrid financing of bank loan and equity. Jin and Zhang (2020) analyzed the conditions that the retailer adopts a hybrid financing mode of bank credit and trade credit and discussed how loss aversion and power imbalance impact the decisions of the supplier and retailer.

In addition to the traditional financing modes mentioned above, financing provided by ECPs and 3PLs is a new financing mode. For example, Chen and Zhang (2019) studied that a capital-constrained retailer can seek financing help from its upstream member or ECP to solve its inventory problem. Yan et al. (2020) researched the decisions of a dual-channel supply chain with capital constraints, where the capital-constrained supplier can obtain financing from the ECP. Furthermore, Yang et al. (2022) analyzed the optimal decisions of supply chain members under the hybrid financing scheme of bank credit and ECP. As for 3PLs financing, Chen and Cai (2011) proved that the 3PL financing can bring higher profits to the whole supply chain and its members. Huang et al. (2018) derived supply chain coordination conditions when the 3PL provide financing services for the capital-constrained retailer. Sun et al. (2022) explored operation and financing decisions in a dual-channel supply chain under ECP financing mode and 3PL financing mode. Although the above studies have discussed the finance modes of a single/dual channel supply chain with capital constraints, there are few studies on the hybrid financing mode of ECP and 3PL.

In recent years, blockchain technology plays an important role in the operation of supply chain. Several scholars have studied the application of blockchain in supply chain according to its characteristics. 1) Traceability. For examples, Tian (2016) and Tian (2017) compared the traceability of blockchain, Internet of thing and RFID. Fan et al. (2020) considered whether the supply chain adopts blockchain technology is linked to the traceability awareness of consumers. Hastig and Sodhi (2020) found the need and importance of blockchain technology traceability. 2) Information disclosure and transparency. For examples, Choi et al. (2020b) explored the impacts of product information disclosure on the consumer surplus and seller benefits. Xu and He (2021) analyzed the effects of information disclosure strategies on the decisions of retail platform and consumers. Wu and Yu (2022) studied the impact of blockchain on platform supply chain from two aspects: information transparency and transaction cost. Zhou et al. (2022) explored that blockchain technology can improve the reliability of information disclosure. Iranmanesh et al. (2022) indicated the intention of SMEs to adopt blockchain is influenced by the contributions of blockchain to supply chain agility and transparency. 3) Sustainability. For examples, Xu et al. (2021) revealed that blockchain technology can not only improve the greenness of products, but also promote the coordination of supply chain to bring more profits to manufacturers and platforms. Xu and Choi (2021) proposed that blockchain technology can trace carbon emissions during production and realize coordination between manufacturers and online platforms. Tao et al. (2022) concluded that the involvement of blockchain technology in production affects product price and quality. Furthermore, the criteria and challenges of blockchain adoption are also studied. For examples, Dehshiri et al. (2022) and Almutairi et al. (2022) evaluated the application criteria and challenges of blockchain technology in the supply chains. Tiwari et al. (2023) identified challenges associated with 3PL and proposed a framework and decision roadmap for implementing BCT in 3PL.

The combination of blockchain and supply chain finance is a hot topic in current research. Choi (2020) proved that compared with traditional supply chain financing, blockchain technology financing can not only reduce operational risks, but also obtain more expected profits. Yu et al. (2020) compared the traditional supply chain financing model of platform undertakes guarantee and the new supply chain financing strategy of customer undertakes guarantee based on blockchain technology. The result indicated that the latter can bring a Pareto improvement. Dong et al. (2022) adopted advance payment (AP) as a financing instrument in a deep-tier supply chain to reduce the supply disruption risk in a traditional system and a blockchain-enabled system. Liu et al. (2021) analyzed the optimal decisions of supply chain members under blockchain platform finance (BPF) and small and medium-sized enterprises independent finance (SIF) compared the two financing models. Choi (2020) researched the product development project financing problem under the initial coin offering case and traditional bank case. Dong et al. (2021) discussed the impact of financial products (i.e., asset-backed securitization) and blockchain on the capital-constrained supply chain decisions. Wang et al. (2023) focused on the financing and operation strategies of the accounts receivable chain for capital-constrained downstream buyers driven by blockchain technology. Most of the above literature discusses the application of blockchain to external bank or institutional financing. However, the application of blockchain to supply chain internal financing literature is relatively rare.

Obviously, there is a lot of literature on supply chain financing modes. At present, the financing modes that they have studied are mainly bank credit, trade credit, mixed bank credit and ECP financing and a mixture of equity and bank credit. However, the literature on the hybrid financing mode of the ECP and 3PL is relatively rare. Although Sun et al. (2022) compared the operation and optimal decisions under the ECP financing mode and the 3PL financing mode, they did not discuss the hybrid financing mode of the ECP and 3PL. In addition, the previous literature mainly uses blockchain to ensure the authenticity and traceability of information and reduce the risk of transaction default. However, the literature considering the impact of blockchain on the information search costs of consumers and the logistics costs of the 3PL is relatively rare. Though Tao et al. (2022) studied that blockchain technology can reduce consumers’ information search costs, they did not study its impact on logistics costs. Different from the above researches, this paper studies how the ECP and 3PL hybrid financing mode and blockchain technology affect the optimal decisions of supply chain members.

This study considers the supply chain composed of a capital-constrained manufacturer, an ECP, a 3PL company, and consumers who want to know product information and compare prices. The manufacture can sell products through the direct channel and the distribution channel. The direct channel is that products produced by the manufacturer are delivered directly to consumers by the 3PL, while the distribution channel is that products produced by the manufacturer are first wholesaled to the ECP, and then the ECP according to the order demand transports products via the 3PL. Due to a lack of capital, the manufacturer needs financing to maintain operations. This paper considers that the funds needed by the manufacturer are provided by the ECP and the 3PL in a certain proportion. Moreover, the two financing parties have different interest rates. Lastly, based on the cost of searching for product information for consumers, we compare the change of the optimal decisions with or without blockchain.

In this paper, the subscript i denotes the sales channel. i = 1 represents the distribution channel, and i = 2 represents the direct channel. The superscript j indicates the scenario. j = N represents that the supply chain does not adopt the blockchain technology, and j = B represents that the supply chain adopts the blockchain technology. The supply chain does not adopt blockchain in Figure 1, but the supply chain adopts blockchain in Figure 2. Table 1 shows the notations and descriptions of this paper.

To analyze and simplify the proposed models, the assumptions and notations made by this paper are as follow.

(1) Based on the previous research (Ghosh and Shah, 2012; Li et al., 2015; Chen et al., 2019; Sun et al., 2022), in scenario N, the demand functions in the ECP distribution channel and the direct sales channel are as follows: D 1 N = a − p 1 N + β p 2 N − s (1) D 2 N = a − p 2 N + β p 1 N − s (2) where s is the cost of information search for consumers, such as the costs of collecting data (Tao et al., 2022).

In scenario B, the demand functions in the ECP distribution channel and the direct sales channel are as follows: D 1 B = a − p 1 B + β p 2 B (3) D 2 B = a − p 2 B + β p 1 B (4)

In all of these functions, a denotes the potential demand for the product in the market, β ( 0 < β < 1 ) denotes the cross-price coefficient between two channels. Note that the order quantity is equal to demand.

(2) According to Jing and Seidmann (2013) and Sun et al. (2022), the initial capital of the manufacturer in this paper is η ( η = 0 ). The wholesale price per unit of product in scenario N is w N , while the wholesale price per unit of product in scenario B is w B .

In scenario N, the decision sequence of the supply chain members is as follows. In terms of interest rates, the ECP first determines the interest rate, and then the 3PL determines the interest rate. In terms of prices, the ECP determines its sales price of the distribution channel, and then the manufacturer decides the wholesale price and the sales price of the direct channel. The profit functions of the manufacturer and the ECP can be expressed, namely, π M N = w N − c N D 1 N + p 2 N − t N − c N D 2 N − γ c N D 1 N + D 2 N 1 + r P N − 1 − γ c N D 1 N + D 2 N 1 + r L N (5) π P N = p 1 N − t N − w N D 1 N + γ r P N c N D 1 N + D 2 N (6) π L N = t N D 1 N + t N D 2 N + 1 − γ r L N c N D 1 N + D 2 N (7)

Based on the principle of profit maximization and the inverse solution method, we can obtain the following lemma and corollary.

Lemma 1

In scenario N, (i) the optimal wholesale price, distribution price of the ECP and sales price of the manufacturer are as follows: w N * = 1 4 1 + β a − s 1 − β − 1 + β t N + c N 3 − β 2 + 1 − γ r L N + 2 γ 2 − β r P N (8) p 1 N * = 1 4 3 − β a − s 1 − β + 1 + β t N + c N 2 + 1 − γ r L N + 2 β γ c N r P N (9) p 2 N * = 1 2 a − s 1 − β + t N + c N 2 + 1 − γ r L N + γ r P N (10)

(ii) The optimal demand of the distribution sales channel and the direct sales channel are as follows: D 1 N * = 1 4 a − s + β − 1 t N + c N 2 + 1 − γ r L N (11) D 2 N * = 1 4 2 + β a − s + β 2 + β − 2 t N + c N 2 + 1 − γ r L N + 2 γ β 2 − 1 c N r P N (12)

Corollary 1

The optimal wholesale price, distribution price, direct sales price, distribution demand and direct sales demand have the following properties: (i) ∂ p 1 N * ∂ s < ∂ p 2 N * ∂ s < ∂ w N * ∂ s < 0 , ∂ p 2 N * ∂ t N > ∂ p 1 N * ∂ t N > 0 > ∂ w N * ∂ t N , ∂ w N * ∂ r P N > ∂ p 2 N * ∂ r P N > ∂ p 1 N * ∂ r P N > 0   a n d   ∂ w N * ∂ r L N > ∂ p 2 N * ∂ r L N > ∂ p 1 N * ∂ r L N > 0 (ii) ∂ D 2 N * ∂ s < ∂ D 1 N * ∂ s < 0 , ∂ D 2 N * ∂ t N < ∂ D 1 N * ∂ t N < 0 , ∂ D 2 N * ∂ r P N < 0   a n d   ∂ D 2 N * ∂ r L N < ∂ D 1 N * ∂ r L N < 0

The following findings can be concluded from Corollary 1. First, all prices are negatively correlated with the cost of information search for consumers. This means that both the sales prices of two channels and the wholesale price will decrease as the information search costs increase. In addition, information search costs have a greater impact on the sales price of distribution channel than that of direct sales channel.

Second, the sales price of the two channels increases with the increase of logistics costs, while the wholesale price decreases as logistics costs increase. Simultaneously, the logistics cost has a greater impact on sales price than demand in two channels. This means that when logistics costs increase, the manufacturer and the ECP will raise their sales price to gain more profits.

Third, all prices are positively correlated with the interest rate of financing for both the ECP and the 3PL. As a result, the manufacturer and the ECP will raise prices regardless of who raises the interest rate. Moreover, the interest rates of the ECP and 3PL have a greater impact on wholesale price and direct sales price because their increase directly affects the manufacturer’s decisions.

Lastly, consumer information search costs, logistics costs and the interest rate of the 3PL have a negative impact on the demand of two channels. Besides, the increase of interest rate of the ECP will reduce the demand of the direct channel, but it will not affect the demand of the distribution channel.

According to the results of Lemma 1, the optimal profit of each supply chain member is as follows: π M N * = 5 + 3 β 16 1 − β { a − s + β − 1 c N 2 + r L N + t N + 1 − β 5 + 3 β γ c N 5 + 3 β r L N − 4 1 + β r P N 2 + γ 2 1 − β 2 1 + β 4 5 + 3 β c N r P N 2 (13) π P N * = 1 8 a − s + β − 1 c N 2 + r L N + t N − γ c N β − 1 r L N − 2 1 + β r P N 2 − 1 + β γ 2 c N r P N 2 (14) π L N * = 1 4 t N + 1 − γ c N r L N 3 + β a − s + β − 1 c N 2 + r L N + t N − γ β − 1 c N 3 + β r L N − 2 1 + β r P N (15)

According to Eqs 13–15, we can obtain the optimal profit of the whole supply chain: π S C N * = 7 + β 16 1 − β a − s + β − 1 c N 2 + r L N + t N + γ 1 − β c N r L N 2 − 1 4 1 − β 2 γ 2 c N r P N 2 + 1 4 t N + 1 − γ c N r L N 3 + β a − s + β − 1 c N 2 + r L N + t N − γ β − 1 c N 3 + β r L N − 2 1 + β r P N (16)

Corollary 2

The profit functions of each supply chain member and the whole supply chain have the following characteristics, respectively: ∂ π M N * ∂ s < 0 , ∂ π P N * ∂ s < 0 , ∂ π L N * ∂ s < 0 , ∂ π S C N * ∂ s < 0 .

Corollary 2 manifests that the increase in consumer information search costs has an adverse effect on the profits of each member of the supply chain and the whole supply chain. The reason is that the increasing of information search costs leads to a decrease in prices and demand, which makes profits reduction.

Next, we analyze the interest rates of the ECP and 3PL. Through the optimal solutions of Lemma 1, the following profit functions can be derived: π P N = p 1 N * − t N − w N * D 1 N * + γ r p N c N D 1 N * + D 2 N * (17) π L N = t N D 1 N * + t N D 2 N * + 1 − γ r L N c N D 1 N * + D 2 N * (18)

By solving Eqs 17, 18, we are able to obtain the following proposition.

Proposition 1

If the optimal interest rates exist (i.e., 0 < r P N , r L N < 1 ), then the optimal interest rates of the ECP and the 3PL are as follows: r P N * = a − s + 2 c N β − 1 4 c N γ 1 − β (19) r L N * = a − s + 2 β − 1 c N + t N 2 c N 1 − γ 1 − β (20)

Considering that 0 < r P N * , r L N * < 1 , thus if 0 < γ < c N + t N 3 c N , we have s + 2 1 − β c N + t N < a < s + 2 c N 1 − β 1 + 2 γ ; if c N + t N 3 c N < γ < 1 , we have s + 2 1 − β c N + t N < a < s + 2 1 − β c N 2 − γ + t N .

Corollary 3

The optimal interest rates of the ECP and 3PL have the following characteristics, respectively: (i) ∂ r P N * ∂ s < 0 , ∂ r L N * ∂ s < 0 (ii) ∂ r P N * ∂ c N < 0 , ∂ r L N * ∂ c N < 0 (iii) ∂ r L N * ∂ t N < 0 (iv) ∂ r P N * ∂ γ < 0 , ∂ r L N * ∂ γ > 0

Corollary 3 (i) indicates that the optimal financing interest rates of the ECP and the 3PL declines with the increase of information search cost. This is because the information search cost will directly affect the demand of consumers, and thus indirectly affect the production of the manufacturer. In other words, the increase in information search costs reduces the order volume and the financing needs of the manufacturer, so the ECP and the 3PL will lower the financing interest rates to attract the manufacturer. Similarly, (ii) when production costs increase, the optimal financing interest rates of the ECP and the 3PL will decrease. The reason is that the production costs affect the amount of financing, and then lead to the change of financing interest rates. As a result, the ECP and 3PL should lower interest rates to attract the manufacturer when production costs increase. Furthermore, (iii) the logistics costs are negatively relevant to the interest rate of the 3PL, while they do not change the interest rate of the ECP. This means that the 3PL can raise the financing interest rates by discounting the logistics cost per unit of product. Therefore, when the logistics costs increase, the 3PL should lower the interest rate to attract the manufacturer and the ECP can raise the interest rate appropriately to increase its own profits. Eventually, (iv) the financing interest rate of the ECP decreases as the ratio of financing increases. In contrast, the financing interest rate of the 3PL increases as the ratio of financing increases. Under the circumstances, the ECP and the 3PL will adjust the interest rates based on the amount borrowed by the manufacturer.

In scenario B, the decision order of supply chain members is similar to scenario N. The profit functions of the manufacturer and the ECP can be expressed, namely, π M B = w B − c B D 1 B + p 2 B − t B − c B D 2 B − γ c B D 1 B + D 2 B 1 + r P B − 1 − γ c B D 1 B + D 2 B 1 + r L B − F M (21) π P B = p 1 B − t B − w B D 1 B + γ r P B c B D 1 B + D 2 B − F P (22) π L B = t B D 1 B + t B D 2 B + 1 − γ r L B c B D 1 B + D 2 B − F L (23)

Based on the principle of profit maximization and the inverse solution method, we can obtain the following lemma and corollary.

Lemma 2

In scenario B, (i) the optimal wholesale price, distribution price of the ECP and sales price of the manufacturer are as follows: w B * = 1 4 1 + β a 1 − β − 1 + β t B + c B 3 − β 2 + 1 − γ r L B + 2 γ 2 − β r P B (24) p 1 B * = 1 4 3 − β a 1 − β + 1 + β t B + c B 2 + 1 − γ r L B + 2 β γ c B r P B (25) p 2 B * = 1 2 a 1 − β + t B + c B 2 + 1 − γ r L B + γ r P B (26)

(ii) The optimal demand of the distribution sales channel and the direct sales channel are as follows: D 1 B * = 1 4 a + β − 1 t B + c B 2 + 1 − γ r L B (27) D 2 B * = 1 4 2 + β a + β + β 2 − 2 t B + c B 2 + 1 − γ r L B + 2 γ β 2 − 1 c B r P B (28)

Corollary 4

The optimal wholesale price, distribution price, direct sales price, distribution demand and direct sales demand have the following properties: (i) ∂ p 2 B * ∂ t B > ∂ p 1 B * ∂ t B > 0 > ∂ w B * ∂ t B , ∂ w B * ∂ r P B > ∂ p 2 B * ∂ r P B > ∂ p 1 B * ∂ r P B > 0   a n d   ∂ w B * ∂ r L B > ∂ p 2 B * ∂ r L B > ∂ p 1 B * ∂ r L B > 0 (ii) ∂ D 2 B * ∂ t B < ∂ D 1 B * ∂ t B < 0 , ∂ D 2 B * ∂ r P B < 0   a n d   ∂ D 2 B * ∂ r L B < ∂ D 1 B * ∂ r L B < 0

Corollary 4 shows that the logistics costs positively affect the sales price of the two channels and negatively influence the wholesale price. When the logistics costs increase, the manufacturer will raise the sales price of the direct sales channel, which leads to the decrease of the order quantity of the direct channel. In order to maximize profits, the manufacturer need to reduce the wholesale price to increase the order quantity of the distribution channel. Meanwhile, the ECP will raise the distribution price to maintain profits when the logistics costs increase. Moreover, the interest rate of financing for both the ECP and the 3PL have a positive effect on all prices, which means that the manufacturer and the ECP will raise prices regardless of who raises the interest rate. And when the interest rate of the ECP increases, it has the greatest impact on the wholesale price, followed by the sales price of the direct sales channel, and it has the least impact on the sales price of the distribution channel. In addition, logistics costs and the interest rate of the 3PL are negatively correlated with the demand of two channels. Lastly, the increase of interest rate of the ECP can decrease the demand of the direct channel, but it cannot affect the demand of the distribution channel.

According to the results of Lemma 2, the optimal profit of each supply chain member is as follows: π M B * = 5 + 3 β 16 1 − β { a + β − 1 c B 2 + r L B + t B + 1 − β 5 + 3 β γ c B 5 + 3 β r L B − 4 1 + β r P B } 2 + γ 2 1 − β 2 1 + β 4 5 + 3 β c B r P B 2 − F M (29) π P B * = 1 8 a + β − 1 c B 2 + r L B + t B − γ c B β − 1 r L B − 2 1 + β r P B 2 − 1 + β γ 2 c B r P B 2 − F P (30) π L B * = 1 4 t B + 1 − γ c B r L B { 3 + β a + β − 1 c B 2 + r L B + t B − γ β − 1 c B 3 + β r L B − 2 1 + β r P B } − F L (31)

According to Eqs 29–31, we can obtain the optimal profit of the whole supply chain: π S C B * = 7 + β 16 1 − β a + β − 1 c B 2 + r L B + t B + γ 1 − β c B r L B 2 − 1 4 1 − β 2 γ 2 c B r P B 2 + 1 4 t B + 1 − γ c B r L B × { 3 + β a + β − 1 c B 2 + r L B + t B − γ β − 1 c B 3 + β r L B − 2 1 + β r P B } − F (32)

Next, we analyze the interest rates of the ECP and 3PL. Through the optimal solutions of Lemma 2, the following profit functions can be derived: π P B = p 1 B * − t B − w B * D 1 B * + γ r P B c B D 1 B * + D 2 B * − F P (33) π L B = t B D 1 B * + t B D 2 B * + 1 − γ r L B c B D 1 B * + D 2 B * − F L (34)

By solving Eqs 33, 34, we are able to obtain the following proposition.

Proposition 2

If the optimal interest rates exist (i.e., 0 < r P B , r L B < 1 ), then the optimal interest rates of the ECP and the 3PL are as follows: r P B * = a + 2 c B β − 1 4 c B γ 1 − β (35) r L B * = a + 2 β − 1 c B + t B 2 c B 1 − γ 1 − β (36)

Considering that 0 < r P B * , r L B * < 1 , thus if 0 < γ < c B + t B 3 c B , we have 2 1 − β c B + t B < a < 2 c B 1 − β 1 + 2 γ ; if c B + t B 3 c B < γ < 1 , we have 2 1 − β c B + t B < a < 2 1 − β c B 2 − γ + t B .

Corollary 5

The optimal interest rates of the ECP and 3PL have the following characteristics, respectively: (i) ∂ r P B * ∂ c B < 0 , ∂ r L B * ∂ c B < 0 (ii) ∂ r L B * ∂ t B < 0 (iii) ∂ r p B * ∂ γ < 0 , ∂ r L B * ∂ γ > 0

Corollary 5 (i) demonstrates that the production cost per unit is negatively correlated with the financing interest rates. The reason is that the increase of production cost leads to the increase of financing amount, and the ECP and 3PL will get more profits by reducing the interest rate. Thus, when the cost of production increases, ECP and 3PL need to adjust their own interest rates downward. Likewise, (ii) the interest rate of the ECP is not affected by the change of logistics costs, while the interest rate of the 3PL decreases with the increase of logistics costs. It means that the ECP can increase the interest rate within a reasonable range to gain more profit. Therefore, when logistics costs increase, the 3PL need to adjust its own interest rate downward but the ECP can adjust its own interest rate upward appropriately. Additionally, (iii) the increase of the financing ratio will reduce the interest rate of the ECP and increase the interest rate of 3PL. Hence financiers will make more profits through the adjustment of interest rates.

Corollary 6

In two scenarios, the optimal wholesale price, distribution price, direct sales price, demand of distribution channel and demand of direct sales channel have the following relationship:

(i) ① If s ^ > 0 , then w B * > w N * ;

② If s ^ < 0 and β − 1 1 + β s ^ ≤ s ≤ s max , then w B * ≥ w N * , where s ^ = 1 + β t N − t B + 3 − β 2 c B − c N + 1 − γ c B r L B − c N r L N + 2 γ 2 − β c B r p B − c N r p N s max = a + β − 1 t N + c N β − 1 2 + 1 − γ r L N + 2 γ 1 + β 2 + β r P N

(ii) If β − 1 3 − β s ^ 1 ≤ s ≤ s max , then p 1 B * ≥ p 1 N * , where

Corollary 6 (i) states that the wholesale price of the manufacturer in scenario B is higher than that in scenario N when the consumer’s information search costs are within a certain range. This is because the market demand decreases as the information search costs increases in scenario N, which leads to a decrease in the manufacturer’s wholesale price. Similarly, (ii) and (iii) show that the sales price of the two channels in scenario B is higher than that in scenario N when the information search costs are within a certain range. The reason is that the change of information search costs will affect the demand, and thus affect the sale prices of the manufacturer and the ECP. Specifically, the increase of information search cost will lead to the decrease of demand, and supply chain members need to reduce the sales price in order to obtain more profits. (iv) and (v) indicate that the demand of two channels in scenario B is higher than that in scenario N. The reason is that the increase in information search costs will directly lead to a decrease in demand.

Corollary 7

In two scenarios, the optimal profit of whole supply chain, the manufacturer, the ECP and the 3PL have the following relationship:

(i) If max 0 , s ^ 3 < s < min s ^ 4 , s max , then π S C B * > π S C N * , where

Corollary 7 presents that when certain conditions are met, the profit in scenario B is higher than that in scenario N. (i) shows that when the consumers’ information search costs meet certain condition, the profit of the whole supply chain in scenario B is higher than that in scenario N. This certain condition is related to the potential demand for the product in the market, the cross-price coefficient between two channels, production cost per unit, logistics cost per unit, the financing ratio of the ECP and interest rates. In other words, the supply chain will adopt blockchain technology under this condition. (ii) shows that when the consumers’ information search costs meet certain condition, the manufacture’s profit in scenario B is higher than that in scenario N. (iii) shows that when the consumers’ information search costs meet certain condition, the ECP’s profit in scenario B is higher than that in scenario N. (iv) shows that when the consumers’ information search costs meet certain condition, the 3PL’s profit in scenario B is higher than that in scenario N. These conditions are closely related to information search costs of consumers, production costs of the manufacturer, the intensity of competition between the two channels, the cost of blockchain adoption, transportation costs, interest rates and the potential market demand.