# Value-Added Service for Fashion Product Supply Chain with Overseas Warehouse Logistics Outsourcing

Authors: Jinjin Mou; Shuyun Wang
Journal: Mathematical Problems in Engineering
 (2023)

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## Abstract

To quickly respond to consumer demand, more and more fashion product cross-border e-commerce (CBEC) retailers outsource international logistics to an integrated overseas warehouse logistics provider (OWLP). Due to the scarcity of integrated OWLP, this paper investigates the effect of the Stackelberg game, where the OWLP dominated the supply chain, and the cooperative game where the retailer and the OWLP are consistent with the interests, on pricing, and the comprehensive value-added service (VAS) strategy for a fashion product and explores the effect of demand coefficient factors on decision-making policy and supply chain performance through sensitivity analysis. It is found that the VAS level increases in the decrease of price coefficienta and the service cost coefficient k, in the increase of the service level coefficient b, and sales cycle coefficient T. By adopting the VAS cost-sharing contract, and not only the total profit of the cooperative game is greater than that of the Stackelberg game but also the win-win cooperation between e-commerce retailer and OWLP is realized.


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## Body

## 1. Introduction

Since the 21st century, thanks to the high popularity of the Internet and the application of advanced information technology, cross-border e-commerce (CBEC), as a new international trade model, has been rising rapidly and has now become a new focus and main driving force for the speedy growth of foreign trade. According to customs statistics, China’s CBEC volume reached 1.69 trillion yuan in 2020, an increase of 31.1%, much higher than the national foreign trade growth rate of 1.9% in the same period. Among them, the export was 1.12 trillion yuan, an increase of 40.1%, and the import was 0.57 trillion yuan, an increase of 16.5% (http://www.customs.gov.cn). The number of imported e-commerce users reached 140 million in 2020, an increase of 11.99% over 2019 (http://www.100ec.cn). Among the import products, fashion products represented the top 1 in import user preferences in 2021 (iiMedia research). According to iiMedia research, products purchased the most in CBEC are clothing, shoes, and bags (48.7%), beauty personal care (45.9%), and food and drinks (43.4%). The empirical study of Spain’s fast fashion e-commerce online purchasing intention found that the purchase intention is positively correlated with trust, cost savings, time savings, and perceived value (Escobar-Rodríguez and Bonsón-Fernández, 2017) [1]. In addition to trust value and the product value/price, the green level, and costs associated with risk, traffic, and opportunities are also important influencing factors to market demand (Sana, 2022) [2, 3]. As fashion goods have a short product life cycle, Chen and Notteboom (2012) [4] revealed that a distribution focus is necessary to transfer from cost to service and market response, especially the service quality (Rao et al., 2011) [5]. Therefore, in addition to the digital marketing strategy (Forghani et al., 2022) [6] and the cooperative advertising strategy (Ezimadu, 2020; Zaheri et al., 2020) [7, 8], the development of CBEC necessarily requires a good logistics service system to coordinate the CBEC supply chain (Zhang et al., 2022; Sun, Gu, 2021) [9, 10]. Das Roy and Sana (2021) [11] considered a multiechelon green supply chain system involving a manufacturer’s warehouse, with no cross-border logistics concerned. In detail, CBEC logistics falls into the postal packet, international express service, special-line logistics, overseas warehouse logistics (OWL), etc. Low prices and wide coverage of postal packets have made it a widely used delivery mode for most CBEC retailers, but it is its high loss rate and long cycle time that hinder its further development. Advantageous in reducing costs through scale operation and high distribution efficiency, special-line logistics is acknowledged as the most-effective cost mode over some other modes. However, its distribution destination is limited, and it is preferable only for some large-size CBEC sellers (Sun et al., 2017) [12]. To settle the drawbacks, OWL emerges as its improvement and innovation of the existing cross-border logistics models with the application of new information technology (Zhang and Liu, 2021) [13], and OWL is used, especially for products with the characteristics of obsolescence, such as fashion items and 3C items (Giuffrida et al., 2020) [14].As for the operation of the OWL, it is subject to some regulatory barriers, customs clearance, foreign-language communication, and returns handling, in addition to shipping cost, delivery cost, and delivery options (Gomez-Herrera et al., 2014; Giuffrida et al., 2020) [14, 15]. International outsourcing of OWL is likely to increase, to handle e-commerce shipments (Morganti et al., 2014; Zhang and Liu, 2021) [13, 16], to reduce the risks of the investment in foreign market logistics assets, and clear the local knowledge barriers (Shi et al., 2016; Ren et al., 2020) [17, 18], as well as to minimize operating costs and carbon emissions and to improve service level (Liu and Lyons, 2011; Zhang et al., 2021; Wang et al., 2022) [19–21]. Here, we focus on an integrated OWL, which provides one-stop control and management service for first-way transportation, warehousing, sorting, packaging, goods delivery, and customs declaration/customs clearance, established and operated by the third-party logistics provider, as well as supply chain optimization, goods identification, anticounterfeiting traceability (Lee and Yeon, 2021) [22], logistics real-time tracking, rapid response to consumer demand, customized solution, and other services (Wang, 2018) [23]. All these services are called value-added logistics services, which can help to enhance customers’ perceived value and promote consumption (Wamba, Queiroz, 2020) [24].However, the integrated OWL operation is still new with a silver lining, and some famous e-commerce retailers, like JD.com and VIP.com, begin to try their hand at Global. Currently, VIP.com, a typical cross-border B2C import e-commerce platform for fashion products, outsources its integrated OWL to third-party providers, to deal with constantly changing conditions in the worldwide market (Čiarnienėa and Vienažindienė, 2014; Leung et al., 2018) [25, 26]. Thus, CBEC supply chains have been bringing concerns about seeking high profit and providing value-added logistics services (hereinafter abbreviated as VAS). Different from traditional service, VAS of logistics is the additional value beyond basic value created from single logistics activity to enhance core competencies (Wang, 2018) [23]. Rivera et al. (2016) [27] demonstrated that larger logistics providers show higher levels of collaboration and VAS in logistics clusters. Zhang et al. (2015) [28] examined the impact of VAS on the pricing decisions of a manufacturer for durable products. Dan et al. (2018) [29] studied the VAS competition for warranty service in a dual-channel supply chain comprising a manufacturer and a retailer. Liu et al. (2021) [30] compared the impact of the retail price, VAS level by the e-tailer, and product freshness by the supplier for the e-commerce supply chain with and without information sharing. The impact of platform VAS on pricing decisions are also examined in recent years (Dou and He, 2017; Liu et al., 2019; Zhang et al., 2021) [20, 31, 32]. The aforementioned VASs are extended from the manufacturers’ service, the retail service, or the platform service, rather than VAS from the CBEC logistics integrator. Even if Wang et al. (2021) [33] considered the VAS of reduction in customer cycle time by 3PL, and Zhang, Liu (2021) [13] considered the VAS of high traceability logistics service, their research did not involve comprehensive VAS level.The contributions of the existing previous optimization articles are presented in Table1.Table 1
Summary of the scenarios in the related literature.
Author (s)Price sensitive demandService/VAS sensitive demandVAS (by 3PL) sensitive demandDecision variablesSana (2022)√——Price, order quantity, reorder pointZhang, Ma (2022)√√—Price, order quantity, logistics service levelLiu et al. (2021)√√—Price, retailer VAS, supplier freshness-keeping effortWang et al. (2021)√√√Order quantityZhang et al. (2021)√√—Price, platform VAS levelShi et al. (2021)√——Presale price, regular price, productivityZhang, Liu (2021)√√√Product price, VAS price of high traceability logistics service; capacity of the smart pallet; improved logistics traceability levelZaheri et al. (2020)√——Price, production quantity, national brand name advertising cost, local advertising cost, manufacturer percentage shared in local advertisingLi et al. (2019)√√—Price, retailer service effortSong, He (2019)√√—Price, logistics freshness-keeping effortMa et al. (2019)√√—Price, logistics freshness-keeping effortDan et al. (2018)√√—Product price, manufacturer VAS, retailer VAS, warranty service levelZhang et al. (2015)√√—Product, manufacturer VAS priceDifferent from the aforementioned studies, we intend to introduce the comprehensive VAS level (measured as a percentage of a multiplicative form of the average consistency of customer order cycle time, average traceability of anticounterfeiting delivery, and average customized service rate) offered by an integrated OWLP rather than a single VAS level to study the product/logistics pricing and service policy for a two-echelon fashion product CBEC supply chain. Hence, the comprehensive VAS level is relatively lower. Our work aims to answer the following questions:(1)
For a two-echelon fashion product CBEC supply chain dominated by the integrated OWLP, when the demand rate is considered the impact of VAS level in addition to retail price, fashion rate (Shi et al., 2021) [34] with the additive form rather than the multiplicative form (Cai et al., 2013; Song and He, 2019; Ma et al., 2019) [35–37]. What are the optimal product pricing, the optimal logistics pricing, and the optimal VAS level?(2)
What are the differences of the optimized results between the Cooperative game and the Stackelberg game? And what effects will the major parameters, such as the price coefficient, the service level coefficient, the service effort cost coefficient, and the selling cycle have on the optimized product/logistics price, the VAS level, and the profits of the e-tailers, the OWLP, and the CBEC supply chain under both the Stackelberg game and the Cooperative game?(3)
To motivate the OWLP to improve the service level, how about the range of the e-tailer’s service cost-sharing rate with the integrated OWLP? What effects of the e-tailer’s service cost-sharing rate with the integrated OWLP will have on the ratio of coordinated profit to decentralized profit, the logistics price, the profit of the e-tailers, and the OWLP under the coordinated scenario?The remainder of the paper is organized as follows: Section2 unfolds the problem description, notation, and assumptions. Section 3 constructs and compares two mathematical models of the Stackelberg game and the Cooperative game. In Section 4, simulation and sensitivity analysis are made to illustrate the effectiveness of the presented models. And conclusions are presented in the Section 5.


## 2. Problem Description and Assumptions

In recent years, with the continuous expansion of OWL services and the increase of investment in logistics proprietary assets, more and more e-tailers tend to improve VAS levels through outsourcing integrated OWL to the third-party provider, e.g., VIP.com’s outsourcing of its integrated OWL to a third-party provider in Korea for the growth of its import e-commerce. Under this circumstance, this model intends to establish a two-echelon supply chain consisting of an integrated OWLP and an e-tailer, with fashion products over a finite time horizon. In this supply chain, the e-tailer sells fashion products to consumers, and the integrated OWLP is responsible for providing the whole logistics service to the e-tailer with a VAS effort. Regarding the commodity tariffs and related taxes, they are paid by consumers, which are overlooked in this paper.Referring to Shi et al. (2021) [34], market demand is a function of the product price, VAS level, and fashion rate of the product, i.e., Dp,S,t=A−aP+bS+cθt, of which θt=θo1−t/T. VAS level (hereinafter abbreviated as service level) is comprehensively measured by such dimensions as consistency of customer order cycle, anticounterfeiting traceability, customized service rate, etc. (Panayides and So, 2005) [38]. As service effort rises, service cost cS increases. Hence, cS is a strictly increasing differentiable function S. Here, service effort cost is depicted as cS=1/2kS2 (Li et al., 2019; Zhang and Ma, 2022) [39, 40]. Regarding the parameters, assuming that ak>b2T holds.In the supply chain, both the integrated OWLP and the e-tailer are completely rational and risk-neutral with symmetrical information. The joint optimization of pricing and service level for fashion product CBEC supply chain under Stackelberg game and Cooperative game, and their comparisons are analyzed in depth. The parameters and meanings are shown in Table2.Table 2
List of notations and descriptions.
ParametersDescriptionTFinite-time horizonDtDemand for fashion products in timetAThe inherent demand for fashion productsaThe price coefficient of market demandbThe sensitivity factor of integrated OWLwThe unit wholesale priceθtThe fashion rate of timetθ0The original fashion ratecThe fashionable coefficient for market demandmThe unit cost of integrated OWLkThe cost coefficient of the service levelηThe e-tailer’s cost-sharing rateΠrThe profit of the e-tailerΠlThe profit of the OWLPΠTThe total profit of the CBEC supply chainSuperscriptjThe optimal result, wherej=i indicates the Cooperative game model, j=d indicates the Stackelberg model, and j=c signifies the coordination modelDecision variablesPThe price of cross-border e-tailersLThe price of an integrated OWLPSThe service level of the integrated OWLP


## 3. Modelling Formulation

Based on the aforementioned problem description and assumptions, the total demand for e-tailers in a finite time horizonT is(1)D=∫0TDtdt=A−aP+bS+cθoT−12cθ0T=A−aP+bS+12cθ0T.


### 3.1. Integrated OWLP Dominated the Stackelberg Game

In domestic e-commerce, the platform may integrate the supply chain (Liu et al. 2022) [41], while, in CBEC, due to the scarcity of integrated OWLPs, the integrated OWLP dominates the supply chain in the Stackelberg game here. And hence, in the Stackelberg game scenario, the integrated OWLP is the leader. The integrated OWLP first sets the logistics price and the service level; then, the e-tailer determines the selling price based on the announced decisions by the OWLP. For any given logistics price L and service level S, the total profit of the e-tailer with a finite time horizon T is(2)πr=P−w−LD=P−w−LA−aP+bS+12cθ0T.In (2), the total profit of the e-tailer equals the sales revenue minus the wholesale price and the logistics cost.The profit of the integrated OWLP is expressed as(3)πl=L−mD−12kS2=L−m⋅A−aP+bS+12cθ0T−12kS2.In (3), the profit of the integrated OWLP equals the logistics revenue minus logistics cost and service effort cost.LetLd∗,Sd∗, and Pd∗ be the optimal logistics price, service level, and the selling price, respectively. Let F=A+1/2cθ0, from (2) and (3), by backward sequential decision-making approach, the Hessian matrix H1 of πl is obtained:(4)H1=−aTbT2bT2−k2×2=akT−14b2.Assuming thatak>b2T, then the Hessian matrix H1 is negative definite, which implies that the profit of the logistics provider is jointly concave in L and S.Solving∂πl/∂L=0 and ∂πl/∂S=0, the optimal logistics price and service level yields, respectively,(5)Ld∗=2kF−aw+2ak−b2Tm4ak−b2T,(6)Sd∗=bTF−aw−am4ak−b2T.Substituting (5) and (6) into Pd∗=1/2aF+bSd∗+aw+aLd∗, we obtain the optimal selling price of the retailer.(7)Pd∗=3akF+ak−b2Taw+ama4ak−b2T.


### 3.2. Cooperative Game

In the Cooperative game, the e-tailer and the integrated OWLP are vertically integrated into the same system. The objective of the supply chain is to determine the optimal selling price and the service level, to maximize the total profit. The total profit of the supply chain in finite time horizonT is(8)πT=πr+πl=P−w−mF−aP+bST−12kS2.In (8), the total profit of the supply chain is the sales revenue minus the wholesale cost, logistics cost, and service effort cost.LetSi∗ and Pi∗ be the optimal service level of the OWLP and the selling price of the e-tailer, respectively.From (8), the Hessian matrix H2 of πT is obtained:(9)H2=−2aTbTbT−k2×2=2akT−b2T2>0.Hence, Hessian matrixH2 is negative definite, which implies that πT is jointly concave in SandP. Solving ∂πT/∂P=0,∂πT/∂S=0, we obtain(10)Pi∗=kF+aw+am−b2Tw+m2ak−b2T,(11)Si∗=bTF−aw−am2ak−b2T.Proposition 1.
Ifak>b2T, in the Cooperative game, the optimal product price is lower than that in the Stackelberg game, logistics service level, and the market demand are significantly higher than those in the Stackelberg game. i.e., Pi∗<Pd∗, Si∗>Sd∗,Di∗>Dd∗.Proof.
Substituting equations (5)–(7) into (1) and substituting (10) and (11) into (1), the optimal market demand under both Stackelberg game and Cooperative game yields, respectively,(12)Dd∗=akTF−aw−am4ak−b2T,Di∗=akTF−aw−am2ak−b2T.
Obviously,Si∗>Sd∗,Di∗>Dd∗.(13)Pi∗−Pd∗=kF+aw+am−b2Tw+m2ak−b2T−3akF+ak−b2Taw+ama4ak−b2T=−2kF−aw−amak−b2T2ak−b2T4ak−b2T<0.
Proposition1 is proved.Proposition 2.
Ifak>b2T, in the Cooperative game, the optimal total profits are significantly higher than those in the Stackelberg game, that is πTi∗>πTd∗.Proof.
Substituting equations (5)–(7) into (2) and (3), substituting equations (10) and (11) into (8), the optimal profit of πrd∗, πld∗ under Stackelberg game and the total profit of πTi∗ under Cooperative game yield, respectively, (14)πrd∗=aTk2F−aw−am24ak−b2T2,πld∗=kTF−aw−am224ak−b2T,πTi∗=kTF−aw−am222ak−b2T.
Then,(15)πTi∗−πrd∗+πld∗=2a2k3TF−aw−am24ak−b2T22ak−b2T>0.
Proposition1 is proved.
Proposition2 and Proposition 2 mean that the higher service level and the lower product price in the Cooperative game lead to higher demand, and a higher total profit in turn. Thus, from the system perspective, the Cooperative game outperforms the Stackelberg game. The managerial insights for Proposition 1 and 2 are that it is better for the cross-border e-tailer to establish strategic relationships with the logistics integrator to improve the VAS level, the market demand, and the profits of the system.Proposition 3.
Ifak>b2T holds, the optimal P, S, and πr, πl, and πT decrease in the price coefficient a and the service effort cost coefficient k; the optimal P, S, and πr, πl, and πT increase in the service coefficient b and the selling cycle T under both the Stackelberg game and the Cooperative game.It can be easily proved that∂P∗/∂a<0, ∂S∗/∂a<0, ∂D∗/∂a<0, ∂πrd∗/∂a<0, ∂πld∗/∂a<0, ∂πT∗/∂a<0, ∂P∗/∂k<0, ∂S∗/∂k<0, ∂πrd∗/∂k<0, ∂πld∗/∂k<0 and ∂πT∗/∂k<0; ∂P∗/∂b>0, ∂S∗/∂b>0, ∂πrd∗/∂b>0, ∂πld∗/∂b>0, ∂πT∗/∂b>0, ∂P∗/∂T>0, ∂S∗/∂T>0, ∂πrd∗/∂T>0, ∂πld∗/∂T>0, and ∂πT∗/∂T>0.Proposition 3 means that, the fashion product supply chain should do every effort to reduce the price coefficienta and the service effort cost coefficient k, meanwhile, increase the service coefficient b and the selling cycle T to increase profits of both the supply chain members and the total supply chain. The main managerial insights for the fashion product e-tailer are that (1) the latest fashionable products should be introduced to the market and fashion spillover effect should be created through network momentum to keep the price coefficient reasonably low; (2) instead of constantly changing products and compressing the sales cycle, lower obsolescent products should be chosen by the e-tailers and their sales cycle should be appropriately extended by any promotion effort. The managerial insights for the 3PLs are that the VAS level should be improved through adopting the new information technology, such as the Internet of things and the blockchains, meanwhile reducing the service effort cost.


### 3.3. Service Cost-Sharing Contract for Coordination

The higher the service level provided by the integrated OWLP, the higher cost will cause, asSi∗>Sd∗ holds. The integrated OWLP may not have enough motivation to improve the service level. Therefore, a service cost-sharing contract is designed to coordinate the two participants to achieve Pareto improvement. The e-tailer shares the service cost of the integrated OWLP. The cost-sharing ratio of the e-tailer is η, then, the ratio of the OWLP is 1−η.Under the proposed contract, the profit of the e-tailer is(16)πrc=p−w−L.D−η.12kS2=P−w−LF−aP+bST−η.12kS2.The profit of the OWLP is(17)πlc=L−m⋅D−1−ηkS22=L−mF−aP+bST−1−ηkS22.Under the proposed contract, using the backward sequential decision-making approach, and solvingSc∗=Si∗, we have(18)Lc∗=2k1−ηF−aw−am2ak−b2T+m.Proposition 4.
If the contract parameter2ak4ak−b2T2+2ak−b2T2/4ak−b2T3≤η≤1−2ak−b2T2/4ak−b2T2 holds, the decentralized system of the Stackelberg game can be coordinated and the Pareto improvement can be achieved. That is, πrc≥πrd∗, πlc≥πld∗, or πrc∗/πrd∗, and πlc∗/πld∗ should be more than 1.Proof.
Substituting equations (10), (11), and (18) into equations (2) and (3), the optimal profit of πrc∗, πlc∗ under cost-sharing contract can be obtained, respectively. Pareto improvement requires that πrc≥πrd∗, πlc≥πld∗. Solving the inequalities, we obtain 2ak4ak−b2T2+2ak−b2T2/4ak−b2T3≤η≤1−2ak−b2T2/4ak−b2T2.
Proposition4 means that when the e-tailer promises to share the service effort cost of the integrated OWLP η within the specified range, the integrated OWLP is motivated to improve the service level, as a result of that, the two parties can achieve more profits than those obtained under decentralized decisions of the Stackelberg game.Proposition 5.
The logistics pricing and the profit of the OWLP decrease in the coordination factorη, and the profit of the e-tailer increases in the coordination factor η.It can be easily proved that∂Lc∗/∂η<0, ∂πlc∗/∂η<0, and ∂πrc∗/∂η>0. Proposition 5 is proved.Proposition 5 means that, the e-tailer shares a higher percentage of the service cost, the logistics pricing will be lower, as a result that a lower profit of the OWLP and a higher profit of the e-tailer get, respectively.The managerial insights for Propositions4 and 5 are that the e-tailer should actively share the logistics cost, so as to promote the improvement of service level and obtain more profits through cooperation than those of its own in the Stackelberg game. Especially, the higher percentage of the service cost shared, the more profits of the e-tailer can be shared.


## 3.1. Integrated OWLP Dominated the Stackelberg Game

In domestic e-commerce, the platform may integrate the supply chain (Liu et al. 2022) [41], while, in CBEC, due to the scarcity of integrated OWLPs, the integrated OWLP dominates the supply chain in the Stackelberg game here. And hence, in the Stackelberg game scenario, the integrated OWLP is the leader. The integrated OWLP first sets the logistics price and the service level; then, the e-tailer determines the selling price based on the announced decisions by the OWLP. For any given logistics price L and service level S, the total profit of the e-tailer with a finite time horizon T is(2)πr=P−w−LD=P−w−LA−aP+bS+12cθ0T.In (2), the total profit of the e-tailer equals the sales revenue minus the wholesale price and the logistics cost.The profit of the integrated OWLP is expressed as(3)πl=L−mD−12kS2=L−m⋅A−aP+bS+12cθ0T−12kS2.In (3), the profit of the integrated OWLP equals the logistics revenue minus logistics cost and service effort cost.LetLd∗,Sd∗, and Pd∗ be the optimal logistics price, service level, and the selling price, respectively. Let F=A+1/2cθ0, from (2) and (3), by backward sequential decision-making approach, the Hessian matrix H1 of πl is obtained:(4)H1=−aTbT2bT2−k2×2=akT−14b2.Assuming thatak>b2T, then the Hessian matrix H1 is negative definite, which implies that the profit of the logistics provider is jointly concave in L and S.Solving∂πl/∂L=0 and ∂πl/∂S=0, the optimal logistics price and service level yields, respectively,(5)Ld∗=2kF−aw+2ak−b2Tm4ak−b2T,(6)Sd∗=bTF−aw−am4ak−b2T.Substituting (5) and (6) into Pd∗=1/2aF+bSd∗+aw+aLd∗, we obtain the optimal selling price of the retailer.(7)Pd∗=3akF+ak−b2Taw+ama4ak−b2T.


## 3.2. Cooperative Game

In the Cooperative game, the e-tailer and the integrated OWLP are vertically integrated into the same system. The objective of the supply chain is to determine the optimal selling price and the service level, to maximize the total profit. The total profit of the supply chain in finite time horizonT is(8)πT=πr+πl=P−w−mF−aP+bST−12kS2.In (8), the total profit of the supply chain is the sales revenue minus the wholesale cost, logistics cost, and service effort cost.LetSi∗ and Pi∗ be the optimal service level of the OWLP and the selling price of the e-tailer, respectively.From (8), the Hessian matrix H2 of πT is obtained:(9)H2=−2aTbTbT−k2×2=2akT−b2T2>0.Hence, Hessian matrixH2 is negative definite, which implies that πT is jointly concave in SandP. Solving ∂πT/∂P=0,∂πT/∂S=0, we obtain(10)Pi∗=kF+aw+am−b2Tw+m2ak−b2T,(11)Si∗=bTF−aw−am2ak−b2T.Proposition 1.
Ifak>b2T, in the Cooperative game, the optimal product price is lower than that in the Stackelberg game, logistics service level, and the market demand are significantly higher than those in the Stackelberg game. i.e., Pi∗<Pd∗, Si∗>Sd∗,Di∗>Dd∗.Proof.
Substituting equations (5)–(7) into (1) and substituting (10) and (11) into (1), the optimal market demand under both Stackelberg game and Cooperative game yields, respectively,(12)Dd∗=akTF−aw−am4ak−b2T,Di∗=akTF−aw−am2ak−b2T.
Obviously,Si∗>Sd∗,Di∗>Dd∗.(13)Pi∗−Pd∗=kF+aw+am−b2Tw+m2ak−b2T−3akF+ak−b2Taw+ama4ak−b2T=−2kF−aw−amak−b2T2ak−b2T4ak−b2T<0.
Proposition1 is proved.Proposition 2.
Ifak>b2T, in the Cooperative game, the optimal total profits are significantly higher than those in the Stackelberg game, that is πTi∗>πTd∗.Proof.
Substituting equations (5)–(7) into (2) and (3), substituting equations (10) and (11) into (8), the optimal profit of πrd∗, πld∗ under Stackelberg game and the total profit of πTi∗ under Cooperative game yield, respectively, (14)πrd∗=aTk2F−aw−am24ak−b2T2,πld∗=kTF−aw−am224ak−b2T,πTi∗=kTF−aw−am222ak−b2T.
Then,(15)πTi∗−πrd∗+πld∗=2a2k3TF−aw−am24ak−b2T22ak−b2T>0.
Proposition1 is proved.
Proposition2 and Proposition 2 mean that the higher service level and the lower product price in the Cooperative game lead to higher demand, and a higher total profit in turn. Thus, from the system perspective, the Cooperative game outperforms the Stackelberg game. The managerial insights for Proposition 1 and 2 are that it is better for the cross-border e-tailer to establish strategic relationships with the logistics integrator to improve the VAS level, the market demand, and the profits of the system.Proposition 3.
Ifak>b2T holds, the optimal P, S, and πr, πl, and πT decrease in the price coefficient a and the service effort cost coefficient k; the optimal P, S, and πr, πl, and πT increase in the service coefficient b and the selling cycle T under both the Stackelberg game and the Cooperative game.It can be easily proved that∂P∗/∂a<0, ∂S∗/∂a<0, ∂D∗/∂a<0, ∂πrd∗/∂a<0, ∂πld∗/∂a<0, ∂πT∗/∂a<0, ∂P∗/∂k<0, ∂S∗/∂k<0, ∂πrd∗/∂k<0, ∂πld∗/∂k<0 and ∂πT∗/∂k<0; ∂P∗/∂b>0, ∂S∗/∂b>0, ∂πrd∗/∂b>0, ∂πld∗/∂b>0, ∂πT∗/∂b>0, ∂P∗/∂T>0, ∂S∗/∂T>0, ∂πrd∗/∂T>0, ∂πld∗/∂T>0, and ∂πT∗/∂T>0.Proposition 3 means that, the fashion product supply chain should do every effort to reduce the price coefficienta and the service effort cost coefficient k, meanwhile, increase the service coefficient b and the selling cycle T to increase profits of both the supply chain members and the total supply chain. The main managerial insights for the fashion product e-tailer are that (1) the latest fashionable products should be introduced to the market and fashion spillover effect should be created through network momentum to keep the price coefficient reasonably low; (2) instead of constantly changing products and compressing the sales cycle, lower obsolescent products should be chosen by the e-tailers and their sales cycle should be appropriately extended by any promotion effort. The managerial insights for the 3PLs are that the VAS level should be improved through adopting the new information technology, such as the Internet of things and the blockchains, meanwhile reducing the service effort cost.


## 3.3. Service Cost-Sharing Contract for Coordination

The higher the service level provided by the integrated OWLP, the higher cost will cause, asSi∗>Sd∗ holds. The integrated OWLP may not have enough motivation to improve the service level. Therefore, a service cost-sharing contract is designed to coordinate the two participants to achieve Pareto improvement. The e-tailer shares the service cost of the integrated OWLP. The cost-sharing ratio of the e-tailer is η, then, the ratio of the OWLP is 1−η.Under the proposed contract, the profit of the e-tailer is(16)πrc=p−w−L.D−η.12kS2=P−w−LF−aP+bST−η.12kS2.The profit of the OWLP is(17)πlc=L−m⋅D−1−ηkS22=L−mF−aP+bST−1−ηkS22.Under the proposed contract, using the backward sequential decision-making approach, and solvingSc∗=Si∗, we have(18)Lc∗=2k1−ηF−aw−am2ak−b2T+m.Proposition 4.
If the contract parameter2ak4ak−b2T2+2ak−b2T2/4ak−b2T3≤η≤1−2ak−b2T2/4ak−b2T2 holds, the decentralized system of the Stackelberg game can be coordinated and the Pareto improvement can be achieved. That is, πrc≥πrd∗, πlc≥πld∗, or πrc∗/πrd∗, and πlc∗/πld∗ should be more than 1.Proof.
Substituting equations (10), (11), and (18) into equations (2) and (3), the optimal profit of πrc∗, πlc∗ under cost-sharing contract can be obtained, respectively. Pareto improvement requires that πrc≥πrd∗, πlc≥πld∗. Solving the inequalities, we obtain 2ak4ak−b2T2+2ak−b2T2/4ak−b2T3≤η≤1−2ak−b2T2/4ak−b2T2.
Proposition4 means that when the e-tailer promises to share the service effort cost of the integrated OWLP η within the specified range, the integrated OWLP is motivated to improve the service level, as a result of that, the two parties can achieve more profits than those obtained under decentralized decisions of the Stackelberg game.Proposition 5.
The logistics pricing and the profit of the OWLP decrease in the coordination factorη, and the profit of the e-tailer increases in the coordination factor η.It can be easily proved that∂Lc∗/∂η<0, ∂πlc∗/∂η<0, and ∂πrc∗/∂η>0. Proposition 5 is proved.Proposition 5 means that, the e-tailer shares a higher percentage of the service cost, the logistics pricing will be lower, as a result that a lower profit of the OWLP and a higher profit of the e-tailer get, respectively.The managerial insights for Propositions4 and 5 are that the e-tailer should actively share the logistics cost, so as to promote the improvement of service level and obtain more profits through cooperation than those of its own in the Stackelberg game. Especially, the higher percentage of the service cost shared, the more profits of the e-tailer can be shared.


## 4. Simulation and Sensitivity Analysis

In this section, we shall conduct case study and to sensitivity analysis to examine the impact of key model parameters on equilibrium and supply chain profits.


### 4.1. Simulation Result

VIP.com is a famous Chinese CBEC retailer for fashion products. It has outsourced 4 OWL activities and 6 bonded warehouse logistics activities in South Korea, France, Australia, the United States, and other countries and regions to integrated OWLPs. At present, Korean brands have contributed more than 30% of the total sales volume of the VIP.com. To make deeper comparative analysis on joint decisions of pricing and service between the Stackelberg game and the Cooperative game, Roem clothing online shopping from South Korea to China is selected for simulation. The parameters are as in Table3.Table 3
The parameters of the example.
TmAawbθ0ck30320003055100.9851800By MATLAB, the optimal results from the Stackelberg game and Cooperative game are gained, in terms of the logistics price, service level, product price, and the demand within time horizonT, and the profits are obtained as in Table 4.Table 4
The optimal results.
Optimal resultsLSPDπrπlπStackelberg game7.4437%64.6519964427873113158Cooperative game75%62.50404917712Table4 shows that, Pi∗<Pd∗, Si∗>Sd∗, and Di∗>Dd∗ (Proposition 1), and πTi∗>πTd∗ (Proposition 2). The relatively lower service levels are due to a comprehensive measure of the consistency of customer order cycle time, anticounterfeiting traceability, and customized service. The higher service level and the lower product price in the Cooperative game lead to a higher demand, and a higher total profit in turn.


### 4.2. Sensitivity Analysis

As is known, with the development of consumption upgrading, consumers’ demand for fashion goods has changed from price orientation to service/quality orientation, hence, we only analyse the impact of the decline of price coefficienta, the service cost coefficient k, and the rise of service level coefficient b and the selling cycle T on decision variables and profits to prove the validity of the theoretical model.


#### 4.2.1. The Effect of Price Coefficienta on Decision Variables and Profits

Figure1 confirms that both the product prices and service levels increase in the decrease of price coefficient a, in both the Cooperative game and the Stackelberg game, and the gap is widening gradually. Meanwhile, all profits of the e-tailer and the OWLP and the supply chain increase in the decrease of price coefficient a (Proposition 3 on a). This requires cross-border e-tailers to work hard on product design and texture, focus on mining brand stories, and promoting the high-quality product to decrease the price coefficient a rather than a price war.Figure 1
The effect of price coefficienta on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


#### 4.2.2. The Effect of Service Level Coefficientb on Decision Variables and Profits

Figure2 confirms that the product prices and the service levels increase in the increase of service coefficient b, in both the Cooperative game and the Stackelberg game, and profits of the e-tailer, the OWLP and the supply chain increase (Proposition 3 on b). Thus, in the CBEC supply chain, on the one hand, the e-tailers should actively establish strategic relations with the OWLPs to strengthen the core competitiveness of the supply chain. On the other hand, as an integrated OWLP, it should actively apply advanced information technologies such as blockchain and the Internet of things, to improve value-added services.Figure 2
The effect of service coefficientb on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


#### 4.2.3. The Effect of Logistics Service Cost Coefficientk on Decision Variables and Profits

In practice, with the development of advanced information technology, and with the increase of operation scale, the service effort cost coefficientk will be declined. Figure 3 confirms that the product price and the service level, the profits of the e-tailer and the OWLP and the supply chain increase in the decrease of service effort cost coefficient k (Proposition 3 on k). So, the OWLP should do its best to reduce the service effort cost coefficient k by expanding operation scale and applying advanced information technology to increase logistics efficiency and effectiveness.Figure 3
The effect of service effort cost coefficientk on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


#### 4.2.4. The Impact of Selling CycleT on Decision Variables and Profit

Figure4 confirms that the increase of the selling cycle T has a few impacts on product price, but it can lead to higher service level and profits of the supply chain in both the Stackelberg game and the Cooperative game and can lead to a higher increase in profits for both the e-tailer and the OWLP in the Stackelberg game. That is, in addition to product quality and design, the supply chain should strengthen online publicity and overseas warehouse cloud exhibition, guide high-quality customers to write excellent comments with pictures and texts, and pay attention to consumer feedback and after-sales service, to appropriately extend the sales cycle.Figure 4
The effect of the selling cycleT on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


#### 4.2.5. Range of Coordination Factorη and Sensitivity Analysis

Figure5 demonstrates that when η∈0.6303,0.7570 holds, both the πrc∗/πrd∗ and πlc∗/πld∗ are more than 1 (Proposition 4). That is, after coordination, both parties can achieve more profits than those under decentralized decisions of the Stackelberg game, and hence, win-win relationships can be established for the two parties. Figure 6 confirms that the price of the OWLP decreases with the increase of the coordination factor η shared by the e-tailer, meanwhile, the profits of the OWLP decrease, and the profits of the e-tailer increase (Proposition 5); Figure 6 also demonstrates that after coordination, when η∈0.6303,0.7570 holds, then Lc∗∈5.19,6.33, which is lower than that of the Stackelberg game, and πlc∗∈8731,13285 and πrc∗∈4427,8981, which mean that the lowest profits of both the OWLP and the e-tailer are more than those of the Stackelberg game (Proposition 4). Otherwise, the lower the service effort cost shared by the e-tailer, the higher the logistics pricing, and the higher the profits shared by the OWLP from the total supply chain profits under the coordination scenario. And how about the coordination factor η, it depends on the bargaining power between the e-tailer and the OWLP.Figure 5
The effect ofη on the ratio of coordinated profit to decentralized profit.Figure 6
The effect of the coordination factorη on logistics price (a) and profits of two parties (b).
(a)(b)


## 4.1. Simulation Result

VIP.com is a famous Chinese CBEC retailer for fashion products. It has outsourced 4 OWL activities and 6 bonded warehouse logistics activities in South Korea, France, Australia, the United States, and other countries and regions to integrated OWLPs. At present, Korean brands have contributed more than 30% of the total sales volume of the VIP.com. To make deeper comparative analysis on joint decisions of pricing and service between the Stackelberg game and the Cooperative game, Roem clothing online shopping from South Korea to China is selected for simulation. The parameters are as in Table3.Table 3
The parameters of the example.
TmAawbθ0ck30320003055100.9851800By MATLAB, the optimal results from the Stackelberg game and Cooperative game are gained, in terms of the logistics price, service level, product price, and the demand within time horizonT, and the profits are obtained as in Table 4.Table 4
The optimal results.
Optimal resultsLSPDπrπlπStackelberg game7.4437%64.6519964427873113158Cooperative game75%62.50404917712Table4 shows that, Pi∗<Pd∗, Si∗>Sd∗, and Di∗>Dd∗ (Proposition 1), and πTi∗>πTd∗ (Proposition 2). The relatively lower service levels are due to a comprehensive measure of the consistency of customer order cycle time, anticounterfeiting traceability, and customized service. The higher service level and the lower product price in the Cooperative game lead to a higher demand, and a higher total profit in turn.


## 4.2. Sensitivity Analysis

As is known, with the development of consumption upgrading, consumers’ demand for fashion goods has changed from price orientation to service/quality orientation, hence, we only analyse the impact of the decline of price coefficienta, the service cost coefficient k, and the rise of service level coefficient b and the selling cycle T on decision variables and profits to prove the validity of the theoretical model.


### 4.2.1. The Effect of Price Coefficienta on Decision Variables and Profits

Figure1 confirms that both the product prices and service levels increase in the decrease of price coefficient a, in both the Cooperative game and the Stackelberg game, and the gap is widening gradually. Meanwhile, all profits of the e-tailer and the OWLP and the supply chain increase in the decrease of price coefficient a (Proposition 3 on a). This requires cross-border e-tailers to work hard on product design and texture, focus on mining brand stories, and promoting the high-quality product to decrease the price coefficient a rather than a price war.Figure 1
The effect of price coefficienta on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


### 4.2.2. The Effect of Service Level Coefficientb on Decision Variables and Profits

Figure2 confirms that the product prices and the service levels increase in the increase of service coefficient b, in both the Cooperative game and the Stackelberg game, and profits of the e-tailer, the OWLP and the supply chain increase (Proposition 3 on b). Thus, in the CBEC supply chain, on the one hand, the e-tailers should actively establish strategic relations with the OWLPs to strengthen the core competitiveness of the supply chain. On the other hand, as an integrated OWLP, it should actively apply advanced information technologies such as blockchain and the Internet of things, to improve value-added services.Figure 2
The effect of service coefficientb on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


### 4.2.3. The Effect of Logistics Service Cost Coefficientk on Decision Variables and Profits

In practice, with the development of advanced information technology, and with the increase of operation scale, the service effort cost coefficientk will be declined. Figure 3 confirms that the product price and the service level, the profits of the e-tailer and the OWLP and the supply chain increase in the decrease of service effort cost coefficient k (Proposition 3 on k). So, the OWLP should do its best to reduce the service effort cost coefficient k by expanding operation scale and applying advanced information technology to increase logistics efficiency and effectiveness.Figure 3
The effect of service effort cost coefficientk on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


### 4.2.4. The Impact of Selling CycleT on Decision Variables and Profit

Figure4 confirms that the increase of the selling cycle T has a few impacts on product price, but it can lead to higher service level and profits of the supply chain in both the Stackelberg game and the Cooperative game and can lead to a higher increase in profits for both the e-tailer and the OWLP in the Stackelberg game. That is, in addition to product quality and design, the supply chain should strengthen online publicity and overseas warehouse cloud exhibition, guide high-quality customers to write excellent comments with pictures and texts, and pay attention to consumer feedback and after-sales service, to appropriately extend the sales cycle.Figure 4
The effect of the selling cycleT on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


### 4.2.5. Range of Coordination Factorη and Sensitivity Analysis

Figure5 demonstrates that when η∈0.6303,0.7570 holds, both the πrc∗/πrd∗ and πlc∗/πld∗ are more than 1 (Proposition 4). That is, after coordination, both parties can achieve more profits than those under decentralized decisions of the Stackelberg game, and hence, win-win relationships can be established for the two parties. Figure 6 confirms that the price of the OWLP decreases with the increase of the coordination factor η shared by the e-tailer, meanwhile, the profits of the OWLP decrease, and the profits of the e-tailer increase (Proposition 5); Figure 6 also demonstrates that after coordination, when η∈0.6303,0.7570 holds, then Lc∗∈5.19,6.33, which is lower than that of the Stackelberg game, and πlc∗∈8731,13285 and πrc∗∈4427,8981, which mean that the lowest profits of both the OWLP and the e-tailer are more than those of the Stackelberg game (Proposition 4). Otherwise, the lower the service effort cost shared by the e-tailer, the higher the logistics pricing, and the higher the profits shared by the OWLP from the total supply chain profits under the coordination scenario. And how about the coordination factor η, it depends on the bargaining power between the e-tailer and the OWLP.Figure 5
The effect ofη on the ratio of coordinated profit to decentralized profit.Figure 6
The effect of the coordination factorη on logistics price (a) and profits of two parties (b).
(a)(b)


## 4.2.1. The Effect of Price Coefficienta on Decision Variables and Profits

Figure1 confirms that both the product prices and service levels increase in the decrease of price coefficient a, in both the Cooperative game and the Stackelberg game, and the gap is widening gradually. Meanwhile, all profits of the e-tailer and the OWLP and the supply chain increase in the decrease of price coefficient a (Proposition 3 on a). This requires cross-border e-tailers to work hard on product design and texture, focus on mining brand stories, and promoting the high-quality product to decrease the price coefficient a rather than a price war.Figure 1
The effect of price coefficienta on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


## 4.2.2. The Effect of Service Level Coefficientb on Decision Variables and Profits

Figure2 confirms that the product prices and the service levels increase in the increase of service coefficient b, in both the Cooperative game and the Stackelberg game, and profits of the e-tailer, the OWLP and the supply chain increase (Proposition 3 on b). Thus, in the CBEC supply chain, on the one hand, the e-tailers should actively establish strategic relations with the OWLPs to strengthen the core competitiveness of the supply chain. On the other hand, as an integrated OWLP, it should actively apply advanced information technologies such as blockchain and the Internet of things, to improve value-added services.Figure 2
The effect of service coefficientb on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


## 4.2.3. The Effect of Logistics Service Cost Coefficientk on Decision Variables and Profits

In practice, with the development of advanced information technology, and with the increase of operation scale, the service effort cost coefficientk will be declined. Figure 3 confirms that the product price and the service level, the profits of the e-tailer and the OWLP and the supply chain increase in the decrease of service effort cost coefficient k (Proposition 3 on k). So, the OWLP should do its best to reduce the service effort cost coefficient k by expanding operation scale and applying advanced information technology to increase logistics efficiency and effectiveness.Figure 3
The effect of service effort cost coefficientk on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


## 4.2.4. The Impact of Selling CycleT on Decision Variables and Profit

Figure4 confirms that the increase of the selling cycle T has a few impacts on product price, but it can lead to higher service level and profits of the supply chain in both the Stackelberg game and the Cooperative game and can lead to a higher increase in profits for both the e-tailer and the OWLP in the Stackelberg game. That is, in addition to product quality and design, the supply chain should strengthen online publicity and overseas warehouse cloud exhibition, guide high-quality customers to write excellent comments with pictures and texts, and pay attention to consumer feedback and after-sales service, to appropriately extend the sales cycle.Figure 4
The effect of the selling cycleT on product price (a), service level (b), profits of two parties (c), and profits of total supply chain (d).
(a)(b)(c)(d)


## 4.2.5. Range of Coordination Factorη and Sensitivity Analysis

Figure5 demonstrates that when η∈0.6303,0.7570 holds, both the πrc∗/πrd∗ and πlc∗/πld∗ are more than 1 (Proposition 4). That is, after coordination, both parties can achieve more profits than those under decentralized decisions of the Stackelberg game, and hence, win-win relationships can be established for the two parties. Figure 6 confirms that the price of the OWLP decreases with the increase of the coordination factor η shared by the e-tailer, meanwhile, the profits of the OWLP decrease, and the profits of the e-tailer increase (Proposition 5); Figure 6 also demonstrates that after coordination, when η∈0.6303,0.7570 holds, then Lc∗∈5.19,6.33, which is lower than that of the Stackelberg game, and πlc∗∈8731,13285 and πrc∗∈4427,8981, which mean that the lowest profits of both the OWLP and the e-tailer are more than those of the Stackelberg game (Proposition 4). Otherwise, the lower the service effort cost shared by the e-tailer, the higher the logistics pricing, and the higher the profits shared by the OWLP from the total supply chain profits under the coordination scenario. And how about the coordination factor η, it depends on the bargaining power between the e-tailer and the OWLP.Figure 5
The effect ofη on the ratio of coordinated profit to decentralized profit.Figure 6
The effect of the coordination factorη on logistics price (a) and profits of two parties (b).
(a)(b)


## 5. Main Conclusions and Managerial Insights

### 5.1. Main Conclusions

In order to investigate the effect of the retailing price and the comprehensive VAS level policy for a cross-border e-tailer outsourcing logistics to an overseas warehouse logistics integrator, we first formulated two game models, the cooperative game model and the Stackelberg game model by adding multiple dimensions of retailing price, comprehensive VAS level (measured as a percentage of a multiplicative form of the average consistency of customer order cycle time, average traceability of anticounterfeiting delivery, and average customized service rate), and fashion rate of the product with an additive form to demand rate, suitable for fashion product character. We proved, by mathematical derivation that optimal solutions exist for these models, and conducted a comparative analysis between the Cooperative game model and the Stackelberg game model and outlined the influence of demand coefficient factors on product/logistics price, VAS level, and profits for the two models. Then, we designed a VAS cost-sharing contract to coordinate the benefits of the two parties in the e-commerce system. Thus, CBEC practitioners are enabled to adopt an appropriate strategy based on the influence of regarding parameters with OWL outsourcing.Results and inferences of the study.(1)
We investigated the optimal VAS level, the retail/logistics price, and the related profit by giving different price coefficienta, VAS coefficient b, and VAS cost coefficient k. The results show that under the Stackelberg game the profits of the two parties are greatly influenced by price coefficient a. That is, with lower price coefficient a, the two parties can earn much more profit because of higher price charged with increased market demand. On the contrary, with higher price coefficient a, the two parties will earn lower profit owing to decreased market demand with lower price charged. In the centralized system, the VAS level is greatly influenced by the service coefficient b, and the service cost coefficient k, with a respective positive and negative direction. Moreover, the appropriate extension of the sales cycle T is conducive to the improvement of VAS level and the increase of retailing price and system profits for the two models.(2)
We observed that the total profit of the Cooperative game model is more than that of the decentralized decision system. This implies that cooperation of the two parties is beneficial to the improvement of the VAS level and the total system profit.(3)
We proved that the proposed VAS cost-sharing contract can realize both system coordination and individual coordination for the two parties. This may be an effective strategy for enhancing the VAS level for fashion product e-commerce so as to promote sales.


### 5.2. Managerial Implications and Insights

For the fashion product e-tailer outsourcing overseas warehouse logistics to an integrator, we obtain several managerial implications from the study as follows:(1)
The Cooperative game model for the centralized system results in a lower retail price, and a higher comprehensive VAS level, compared to the Stackelberg game model for the decentralized system, which results in decreased total profit and lower VAS level. Hence, it is advantageous for the cross-border e-tailer to establish strategic relationships with the logistics integrator to improve the VAS level and the performance of the system.(2)
The sensitivity analysis shows that under the Stackelberg game model, products with low price coefficient would increase the profits for both the cross-border e-tailer and the logistics integrator. To stimulate consumers with low price coefficient for fashion products, high VAS level should be rendered by the logistics integrator. So, the fashion product e-tailer should rush the latest fashionable products to the market, or take advantage of the fashion spillover effect created through network momentum/overseas warehouse cloud exhibition, to keep the price coefficient reasonably low. Meanwhile, the logistics integrator should be more aggressive in enhancing the VAS level through adopting the new information technology, such as the Internet of things, the blockchains, and so on. Moreover, since the appropriate extension of the sales cycle is conducive to the increase of system profits for two models, instead of constantly changing products and compressing the sales cycle, lower obsolescent products should be chosen by the e-tailers and their sales cycle should be appropriately extended by any promotion effort for both the e-tailers and the 3PLs.(3)
Based on the VAS cost-sharing contract, both the fashion product e-tailer and the logistics integrator can improve their profits from increased market demand, especially, the higher the service effort cost shared by the e-tailer, the lower the logistics pricing, and the higher the profits obtained by the e-tailer under the coordination scenario.(4)
As consumers pay more attention to VAS, a logistics integrator should continue to elevate its VAS level and reduce the cost of such services, especially with the recent development of blockchain technology.Our work in this study is focused on a two-echelon CBEC supply chain; it can conceivably be extended to subjects involving multilayer supply chains and multivariables. First, the model in our study could be extended to a three-echelon supply chain by adding on the fashion brand enterprise. Second, our model is focused on a monopolistic market and deterministic demand rate; it can be extended to a random and competitive market environment. Hopefully, the results of this study will interest future research to consider the three-echelon supply chain optimization problem with competitive random market demand for fashion product cross-border e-tailers outsourcing logistics to 3PL integrators.


## 5.1. Main Conclusions

In order to investigate the effect of the retailing price and the comprehensive VAS level policy for a cross-border e-tailer outsourcing logistics to an overseas warehouse logistics integrator, we first formulated two game models, the cooperative game model and the Stackelberg game model by adding multiple dimensions of retailing price, comprehensive VAS level (measured as a percentage of a multiplicative form of the average consistency of customer order cycle time, average traceability of anticounterfeiting delivery, and average customized service rate), and fashion rate of the product with an additive form to demand rate, suitable for fashion product character. We proved, by mathematical derivation that optimal solutions exist for these models, and conducted a comparative analysis between the Cooperative game model and the Stackelberg game model and outlined the influence of demand coefficient factors on product/logistics price, VAS level, and profits for the two models. Then, we designed a VAS cost-sharing contract to coordinate the benefits of the two parties in the e-commerce system. Thus, CBEC practitioners are enabled to adopt an appropriate strategy based on the influence of regarding parameters with OWL outsourcing.Results and inferences of the study.(1)
We investigated the optimal VAS level, the retail/logistics price, and the related profit by giving different price coefficienta, VAS coefficient b, and VAS cost coefficient k. The results show that under the Stackelberg game the profits of the two parties are greatly influenced by price coefficient a. That is, with lower price coefficient a, the two parties can earn much more profit because of higher price charged with increased market demand. On the contrary, with higher price coefficient a, the two parties will earn lower profit owing to decreased market demand with lower price charged. In the centralized system, the VAS level is greatly influenced by the service coefficient b, and the service cost coefficient k, with a respective positive and negative direction. Moreover, the appropriate extension of the sales cycle T is conducive to the improvement of VAS level and the increase of retailing price and system profits for the two models.(2)
We observed that the total profit of the Cooperative game model is more than that of the decentralized decision system. This implies that cooperation of the two parties is beneficial to the improvement of the VAS level and the total system profit.(3)
We proved that the proposed VAS cost-sharing contract can realize both system coordination and individual coordination for the two parties. This may be an effective strategy for enhancing the VAS level for fashion product e-commerce so as to promote sales.


## 5.2. Managerial Implications and Insights

For the fashion product e-tailer outsourcing overseas warehouse logistics to an integrator, we obtain several managerial implications from the study as follows:(1)
The Cooperative game model for the centralized system results in a lower retail price, and a higher comprehensive VAS level, compared to the Stackelberg game model for the decentralized system, which results in decreased total profit and lower VAS level. Hence, it is advantageous for the cross-border e-tailer to establish strategic relationships with the logistics integrator to improve the VAS level and the performance of the system.(2)
The sensitivity analysis shows that under the Stackelberg game model, products with low price coefficient would increase the profits for both the cross-border e-tailer and the logistics integrator. To stimulate consumers with low price coefficient for fashion products, high VAS level should be rendered by the logistics integrator. So, the fashion product e-tailer should rush the latest fashionable products to the market, or take advantage of the fashion spillover effect created through network momentum/overseas warehouse cloud exhibition, to keep the price coefficient reasonably low. Meanwhile, the logistics integrator should be more aggressive in enhancing the VAS level through adopting the new information technology, such as the Internet of things, the blockchains, and so on. Moreover, since the appropriate extension of the sales cycle is conducive to the increase of system profits for two models, instead of constantly changing products and compressing the sales cycle, lower obsolescent products should be chosen by the e-tailers and their sales cycle should be appropriately extended by any promotion effort for both the e-tailers and the 3PLs.(3)
Based on the VAS cost-sharing contract, both the fashion product e-tailer and the logistics integrator can improve their profits from increased market demand, especially, the higher the service effort cost shared by the e-tailer, the lower the logistics pricing, and the higher the profits obtained by the e-tailer under the coordination scenario.(4)
As consumers pay more attention to VAS, a logistics integrator should continue to elevate its VAS level and reduce the cost of such services, especially with the recent development of blockchain technology.Our work in this study is focused on a two-echelon CBEC supply chain; it can conceivably be extended to subjects involving multilayer supply chains and multivariables. First, the model in our study could be extended to a three-echelon supply chain by adding on the fashion brand enterprise. Second, our model is focused on a monopolistic market and deterministic demand rate; it can be extended to a random and competitive market environment. Hopefully, the results of this study will interest future research to consider the three-echelon supply chain optimization problem with competitive random market demand for fashion product cross-border e-tailers outsourcing logistics to 3PL integrators.



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*Source: 8798358-2023-02-13.xml*