research article channel coordination in logistics service
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Research ArticleChannel Coordination in Logistics Service Supply Chainconsidering Fairness
Ningning Wang,1 Zhi-Ping Fan,1,2 and Xiaohuan Wang1
1Department of Information Management and Decision Sciences, School of Business Administration,Northeastern University, Shenyang 110169, China2State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China
Correspondence should be addressed to Xiaohuan Wang; [email protected]
Received 11 January 2016; Accepted 6 March 2016
Academic Editor: Sri Sridharan
Copyright ยฉ 2016 Ningning Wang et al.This is an open access article distributed under the Creative CommonsAttribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Logistics service supply chain (LSSC) is a new type of service supply chain.This paper investigates the channel coordination issue ina two-echelon LSSC composed of one logistics service integrator (LSI) and one functional logistics service provider (FLSP) underfairness concerns.Themodels for a reservation price-only contract under disadvantageous inequality and advantageous inequalityare established, respectively, in which the procurement cost, the potential shortage cost, and the operation cost are consideredunder stochastic market demand. Based on this model, the LSIโs optimal reservation quantity can be determined. Furthermore, weanalyze the impact of fairness concerns and the related costs on channel performance and channel coordination. The results arepresented in four aspects: (1) channel coordination of the LSSC can be achieved under certain conditions when the LSI experiencesadvantageous inequality; (2) the spiteful behavior of the LSI leads to the reduction of the channel profit, and channel coordinationcannot be achieved when the LSI suffers from disadvantageous inequality; (3) the LSIโs reservation quantity and the channel profitare affected by the LSIโs fairness concerns; (4) motivated by the concerns of fairness, the LSIโs reservation quantity is related notonly to his procurement cost and shortage cost but also to the FLSPโs operation cost.
1. Introduction
Logistics service supply chain (LSSC) refers to a logistics ser-vice network structurewhich is connected from the front-endfunctional logistics service providers (FLSPs) to the logisticsservice integrators (LSIs) and to customers (manufacturersor retailers) [1, 2]. It is an important branch of servicesupply chain focused on the cooperation of logistics servicecapacities [3, 4]. In the freight distribution channel, the FLSPand the LSI are urged to work efficiently and collaborativelyto maintain their competitiveness [5]. Traditionally, the LSItends to reserve enough logistics service capacity (e.g., aircargo spaces or container trucks) from the FLSP and then sat-isfies the market demands of customers. For example, ChinaCOSCO logistics company reserves railway transportationservice and airline transportation service from TRAINOSEcompany of Greece and China Southern Airlines (CSA),respectively. Then he provides the comprehensive logisticsservice to several giants of appliances manufacturers such as
Haier, TCL, and Changhong. In this LSSC, TRAINOSE andCSA play the role of FLSP, while COSCO plays the role ofLSI.
In general, the traditional supply chain refers to anintegrated manufacturing process including purchasing rawmaterials, processing raw materials into final products, anddistributing the final products to end customers [6, 7],while the LSSC refers to a cooperation process of logisticsservice capacity, where logistics service is an execution ofactivity, rather than a tangible asset. Obviously, there aremany differences between the traditional supply chain andthe LSSC. In a LSSC, the LSI owns the access right of theFLSPโs assets (e.g., air cargo spaces or container trucks)rather than the ownership. Thus, the unused logistics servicecapacity is hard to be resold to the other LSI(s) or FLSP(s)since the negotiation process between the companies (e.g.,the LSI and the FLSP) is complicated and the negotiationcost is high; that is, the unused logistics service capacityis costly to be handled as salvage value. Moreover, the
Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2016, Article ID 9621794, 15 pageshttp://dx.doi.org/10.1155/2016/9621794
2 Mathematical Problems in Engineering
logistics service has the characteristics such as nonstorage,perishability, and demand uncertainty [8โ10]. Hence, the LSIwould bear more market risk under the uncertain marketdemand.
In the LSSC, the conflict and competition widely existin the cooperation of logistics service capacities since theLSI and the FLSP are independent economic entities [11].Therefore, channel coordination issue of the LSSC hasincreasingly caught the attentions in supply chain studies[4, 11]. The objective of channel coordination is to reducethe negative effects of conflict and demand uncertainty andeventually improve the performance of the supply chain[12โ14].
The supply chain coordination issue considering fairnessconcerns is a new research topic in recent years [15โ18].The existing studies have shown that firms care not onlyabout their own profits but also about whether the profitallocation of the entire channel is fair or not [19โ21], thatis, fairness concerns [22]. Usually, firms tend to penalizethe unfair behaviors even at the cost of paying expense [16,17, 23]. In a LSSC, the LSI may reduce (or increase) thereservation quantity of logistics service to punish (or reward)the FLSP if he feels unfair. In addition, fairness concerns playan important role in developing and maintaining channelrelationship [24], while the sound cooperative relation in aLSSC can reduce the transaction cost and the cooperative risk[25].
Therefore, based on the current studies about supplychain coordination with fairness concerns, whether the profitallocation in the LSSC is fair or not is also a noteworthyproblem. Furthermore, given the differences between thetraditional supply chain and the LSSC, we would like to focuson several interesting questions: How does the LSI decidethe reservation quantity of logistics service under fairnessconcerns? How do fairness concerns influence the profitallocation in a LSSC? Whether a simple reservation price-only contract can effectively coordinate the LSI and the FLSPunder fairness concerns? If it can, what fairness preferenceand condition can guarantee the LSSC coordination? How dothe related costs (e.g., the LSIโs procurement cost and shortagecost and the FLSPโs operation cost) impact the LSIโs reservingdecision towards logistics service capacity?
Two streams of the literature are most closely related tothe research issue we are concerned with. The first streamfocuses on the channel coordination issue of the LSSC(see [4, 11, 25]). For example, Liu et al. [4] investigatehow to determine the fairest revenue-sharing coefficient forthe revenue-sharing contract in the LSSC under stochasticdemand. By modeling a Stackelberg differential game, Zhaoet al. [11] show that the cost sharing contract is an effectivecoordination mechanism in a LSSC. The second streaminvestigates the role of fairness concerns in the traditionalsupply chain (see [15โ18, 24, 26, 27]). For example, Cui etal. [15] adopt the disutility factor and the equitable payofffactor to depict fairness concerns and investigate how fairnessconcerns impact channel coordination in a dyadic channelunder linear demand. Caliskan-Demirag et al. [26] extend theCui et al.โs [15] model to the situation of nonlinear demand.Similar to the findings of Cui et al. [15] andCaliskan-Demirag
et al. [26], Yang et al. [24] find that co-op advertising cancoordinate the entire channel in some cases when the retailerhas fairness concerns. Du et al. [16] investigate how thefairness preference impacts the channel efficiency by intro-ducing Nash bargaining solution as the fairness referencepoint. Wu and Niederhoff [18] analyze the impact of fairnessconcerns for the two-stage random demand newsvendormodel.
Our study is different from the above two streamsof literature. Comparing to the first literature stream, weconsider adopting the fair utility function to describe theLSIโs fairness concerns and focus on the impact of the LSIโsfairness concerns on the channel performance and channelcoordination. Also, we focus on the reservation price-onlycontract rather than the revenue-sharing contract or the costsharing contact, since the reservation price-only contract issimple and the incentive contract in the real world frequentlytakes simpler form than what theory often predicts [28โ30]. Comparing to the second literature stream, there aretwo main differences in our study. On the one hand, forthe LSSC, the existing studies about the fairness analysis inthe traditional supply chain could be unsuitable to someextent since the LSI faces more market risks than the retailerin the traditional supply chain. Thus, we focus on howfairness concerns impact channel performance and channelcoordination in a LSSC. On the other hand, most of theexisting studies about the fairness analysis in supply chainrarely consider the procurement cost, the potential shortagecost, and the salvage value under stochastic market demand,which are major concerns that could affect the channelmembersโ decisions in reality [31โ33]. Thus, to be moreclose to the reality, we attempt to build the fairness modelconsidering the above-mentioned costs and the operationcost as well.
In this paper, wewill start with a benchmarkmodel.Then,based on the benchmarkmodel, the reservation price modelsconsidering the LSIโs fairness concerns are established; thatis, two decentralized models are established under disadvan-tageous inequality and advantageous inequality, respectively.Through the established models, we derive the closed-formexpression of the optimal reservation quantity and investigatethe impacts of fairness concerns and the related costs (e.g.,the LSIโs procurement cost and shortage cost and the FLSPโsoperation cost) on channel performance and channel coordi-nation.
The major contributions of our study to the research areas follows: we introduce fairness concerns into a two-echelonLSSC and investigate the impacts of fairness concerns on theLSIโs reservation quantity, the channel profit, and the channelcoordination. We build the fairness model considering theLSIโs procurement cost, the potential shortage cost andsalvage value, and the FLSPโs operation cost under stochasticdemand and discuss the impacts of the procurement cost,the shortage cost, and the FLSPโs operation cost on theLSIโs reservation quantity in detail. Also, we give somevaluable management insights for the practices of channelcoordination in the LSSC.
The remainder of the paper is organized as follows.In Section 2, we describe the problem and give the
Mathematical Problems in Engineering 3
assumptions and notations used in this paper. In Section 3,we first present the benchmark model, and then we establishthe decentralized models under disadvantageous andadvantageous inequality. Further, we analyze the impactsof fairness concerns and the related costs on channelperformance and channel coordination. In Section 4, severalnumerical examples are presented to validate the modelsand the analysis results. Finally, the conclusions of our studyand the directions for the future research are presented inSection 5.
2. Assumptions and Notations
In this paper, we consider a one-period two-echelon LSSCcomposed of one FLSP (she) and one LSI (he). Weassume that the market demand of logistics service isstochastic because of demand uncertainty of logistics service.Let ๐ท denote the market demand throughout the sellingseason,๐ท > 0, and๐ท is drawn from a continuous and differ-entiable cumulative distribution function ๐น(๐ฅ) with positivedensity ๐(๐ฅ), ๐น(0) = 0, and ๐ = ๐ธ[๐ท]. Before the sellingseason, the LSI needs to determine the reservation quantity๐ of logistics service from the professional FLSP according tohis market demand predictions. The FLSP supplies the LSIwith the logistics service capacity at the reservation price๐ค per unit. Then the LSI sells comprehensive logisticsservice to his customers at a unit price ๐. Here, both ๐ and๐ค are exogenous. In this way, the LSI will incur marginalprocurement cost ๐
๐, such as the administrative expenses
during the procurement process; meanwhile, the FLSP willincur relevant operation cost ๐
๐for offering logistics service
capacity. Furthermore, the LSI will pay a goodwill penaltycost ๐
๐ (shortage cost) to customers when he lacks logis-
tics service capacity. When the LSI has surplus capacity,the LSI earns the salvage value V
๐per unit of unused
logistics service capacity at the end of season. We assumethat V
๐can be deemed as zero since the unused logis-
tics service cannot be stored or is costly to be resold tothe other LSI(s) or FLSP(s). Thus, the LSI would bearall the potential risks caused by capacity shortage or sur-plus in the situation of uncertain market. In view of theactual situation, without loss of generality, we assume that๐๐ > ๐ค > ๐
๐> ๐๐.
In the problem that we are concerned with, we assumethat both the FLSP and the LSI are risk-neutral andinformation-symmetrical. The LSI has his own fairnessbenchmark; that is, the equitable outcome for the LSI is ๐พtimes the FLSPโs outcome.That is to say, the LSI will perceivedisadvantageous inequality if his profit is less than ๐พ timesthat of the FLSPโs outcome; in the meantime, he will perceiveadvantageous inequality if his profit is greater than ๐พ timesthat of the FLSPโs outcome. Specifically, we follow the sameroute as Cui et al. [15]; the LSIโs expected utility ๐
๐ผcan be
expressed by
๐๐ผ= ฮ ๐ผโ ๐ผmax {๐พฮ
๐นโ ฮ ๐ผ, 0}
โ ๐ฝmax {ฮ ๐ผโ ๐พฮ ๐น, 0} ,
(1)
where ฮ ๐ผand ฮ
๐นdenote the expected profits of the LSI
and the FLSP, respectively. ๐ผ, ๐ฝ, and ๐พ are three coefficientsdepicting fairness concerns. ๐ผ denotes the measurement ofthe LSIโs disutility or inequity-averse degree if his profit isless than his equitable outcome [18], ๐ผ > 0. ๐ฝ denotesthe measurement of the LSIโs disutility or inequity-aversedegree if his profit is greater than his equitable outcome[18, 34], ๐ฝ โค ๐ผ and 0 < ๐ฝ < 1. ๐พ denotes the degreeof LSIโs perceived relative advantage against the FLSP anddepends on the factors such as the outside options and soon [15, 27], ๐พ > 0. Specially, the larger the LSIโs perceivedrelative advantage against the FLSP is, the bigger the ๐พ willbe.
To facilitate the following analysis, we summarize the keynotations as shown in the following part.
Variable Definitions
๐ท: market demand of logistics service,๐(๐ฅ): probability density function of market demand๐ท,๐น(๐ฅ): cumulative distribution function of marketdemand๐ท,๐๐: LSIโs marginal procurement of logistics service
capacity,๐๐: FLSPโs unit operation cost of logistics service
capacity,๐๐ : the unit shortage cost of insufficient logistics
service capacity,V๐: the unit salvage value of unused logistics service
capacity,๐ค: reservation price per unit of logistics servicecapacity,๐: selling price per unit of logistics service capacity,๐: LSIโs reservation quantity of logistics service,๐ผ, ๐ฝ, and ๐พ: coefficients in the utility function (1),ฮ ๐ผ: expected profit of LSI,
ฮ ๐น: expected profit of FLSP,
ฮ ๐ฟ: expected profit of entire LSSC.
3. Model Formulation
Given that the market demand of logistics service is stochas-tic, the LSIโs expected sales ๐ (๐) are given by ๐ (๐) = ๐ โ
โซ๐
0
๐น(๐ฅ)๐๐ฅ; the LSIโs expected lost-sales ๐(๐) are given by๐(๐) = ๐ โ ๐ + โซ
๐
0
๐น(๐ฅ)๐๐ฅ if ๐ < ๐ท (the LSIโs reservedquantity of logistics service is less than the market demand),and the LSIโs expected unused capacity โ(๐) is given by โ(๐) =โซ๐
0
๐น(๐ฅ)๐๐ฅ if ๐ > ๐ท. In this section, the centralized modeland the decentralized model are constructed, which serve asthe benchmark to evaluate channel coordination in the LSSCunder fairness concerns. Further, the channel coordinationmodels are established when the LSI experiences disadvan-tageous and advantageous inequality, respectively. On the
4 Mathematical Problems in Engineering
basis of these models, some analyses are given correspond-ingly.
3.1. Benchmark Model. In the centralized setting, the LSI andthe FLSPmake decision together, and they hope to maximizethe entire channel profit. Thus, the profit of the entire LSSCcan be formulated as
๐๐ฟ= ๐min (๐, ๐ท) โ (๐
๐+ ๐๐) ๐ โ ๐
๐ (๐ท โ ๐)
+
+ V๐(๐ โ ๐ท)
+
.
(2)
Since the unused logistics service capacity cannot be storedor is costly to be resold to the other companies, the salvagevalue of the unused logistics service capacity can be deemedas zero; that is, V
๐= 0. Thus, the expected profit of the entire
LSSC can be expressed as
ฮ ๐ฟ= ๐๐ โ ๐โซ
๐
0
๐น (๐ฅ) ๐๐ฅ โ (๐๐+ ๐๐) ๐ โ ๐๐
๐ + ๐๐ ๐
โ ๐๐ โซ๐
0
๐น (๐ฅ) ๐๐ฅ.
(3)
Since ๐2ฮ ๐ฟ/๐๐2 < 0, ฮ
๐ฟis concave with respect to ๐.
Therefore, the optimal reservation quantity of the LSSC canbe obtained; that is,
๐โ
cen = ๐นโ1
(1 โ๐๐+ ๐๐
๐ + ๐๐
) . (4)
In the traditional decentralized setting, all participantsmaximize their individual profits without considering anyfairness issues. The sequence of events in this game is asfollows: the FLSP offers the LSI a reservation price-onlycontract, and then the LSI determines whether the contract isaccepted or not. If the LSI accepts the contract, hewill seek theoptimal reservation quantity of logistics service to maximizehis own profit; if the LSI rejects the contract, the game endsand each participant will earn a default payoff.Thus, the LSIโsprofit can be given by
๐๐ผ= ๐min (๐, ๐ท) โ (๐ค + ๐
๐) ๐ โ ๐
๐ (๐ท โ ๐)
+
+ V๐(๐ โ ๐ท)
+
.
(5)
Taking V๐= 0 into account, the LSIโs expected profit can be
formulated as
ฮ ๐ผ= ๐๐ โ ๐โซ
๐
0
๐น (๐ฅ) ๐๐ฅ โ (๐ค + ๐๐) ๐ โ ๐๐
๐ + ๐๐ ๐
โ ๐๐ โซ๐
0
๐น (๐ฅ) ๐๐ฅ.
(6)
The FLSPโs expected profit can be formulated as
ฮ ๐น= ๐ค๐ โ ๐
๐๐. (7)
Since ๐2ฮ ๐ผ/๐๐2 < 0, ฮ
๐ผis concave with respect to ๐.
Therefore, the optimal reservation quantity of the LSI can beobtained; that is,
๐โ
dec = ๐นโ1
(1 โ๐ค + ๐๐
๐ + ๐๐
) . (8)
Given that ๐ค > ๐๐, it can be seen from (4) and (8) that
๐โcen > ๐โ
dec. Thus, the reservation quantity in the decentral-ized setting is not equal to the one in the centralized settingdue to the double marginalization problem. In other words,the double marginalization problem cannot be eliminatedunless the FLSPโs profit is zero (i.e., ๐ค = ๐
๐). Obviously,
the LSSC cannot be coordinated by the reservation price-only contract when the LSIโs procurement cost, the potentialshortage cost and salvage value, and the FLSPโs operation costare considered. Also, through the comparison and analysis,we find that the optimal reservation quantity of the LSI issmaller than that of the retailer from a classical newsvendorproblem when the LSI faces a greater market risk [12]. Inother words, the optimal reservation quantity of the LSI indecentralized setting even derives from that in the centralizedsetting.
3.2. Model with the LSIโs Fairness Concerns. We restrictour attention to a scenario that the LSI is fair-minded inthe decentralized LSSC. Since the FLSPโs objective is tomaximize his profit, her utility is equivalent to her profit.The sequence of events of the game is as follows: the FLSPfirst provides a reservation price-only contract to the LSI;then, by observing the stochastic demand, the LSI decideswhether the contract is accepted or not. If he accepts,he must make the decision about the reservation quantityof logistics service to maximize his utility; otherwise, thegame ends. To describe the LSIโs expected utilities underdisadvantageous and advantageous inequality, respectively,(1) can be expressed in the form of a piecewise function; thatis,
๐๐ผ={
{
{
(1 + ๐ผ)ฮ ๐ผโ ๐ผ๐พฮ
๐น, for ฮ
๐ผโค ๐พฮ ๐น,
(1 โ ๐ฝ)ฮ ๐ผ+ ๐ฝ๐พฮ
๐น, for ฮ
๐ผโฅ ๐พฮ ๐น.
(9)
From (9), if the LSIโs profit is smaller than his equitableoutcome, that is, ฮ
๐ผโค ๐พฮ ๐น, then he suffers from disadvan-
tageous inequality and behaves spitefully; if the LSIโs profitis greater than his equitable outcome, that is, ฮ
๐ผโฅ ๐พฮ ๐น, he
experiences advantageous inequality and behaves generously.
3.2.1. Disadvantageous Inequality. If the LSI accepts theFLSPโs reservation price-only contract and his payoff issmaller than ๐พ times that of the FLSPโs outcome, then the LSIwill determine a desirable reservation quantity to maximizehis utility. Thus, according to (6), (7), and (9), the opti-mization problem faced by the LSI under disadvantageousinequality can be defined as
Mathematical Problems in Engineering 5
max๐โฅ0
๐๐ผ
dis = (1 + ๐ผ)ฮ ๐ผ โ ๐ผ๐พฮ ๐น
= (1 + ๐ผ) [๐๐ โ ๐โซ๐
0
๐น (๐ฅ) ๐๐ฅ โ (๐ค + ๐๐) ๐ โ ๐๐
๐ + ๐๐ ๐ โ ๐๐ โซ๐
0
๐น (๐ฅ) ๐๐ฅ] โ ๐ผ๐พ (๐ค โ ๐๐) ๐.
(10)
By (10), we can get the following propositions.
Proposition 1. If the LSI suffers from disadvantageousinequality under the reservation price-only contract, then theoptimal reservation quantity, ๐โ
๐๐๐ , is
๐โ
๐๐๐ = ๐นโ1
(1 โ(1 + ๐ผ) (๐ค + ๐
๐) + ๐ผ๐พ (๐ค โ ๐
๐)
(1 + ๐ผ) (๐ + ๐๐ )
) . (11)
The proof of Proposition 1 is provided in Appendix.Proposition 1 indicates that the LSIโs expected utility, ๐๐ผdis, isstrictly concave with respect to ๐. That is to say, when heaccepts the reservation price-only contract and suffers fromdisadvantageous inequality, his optimal reservation quantityis ๐โdis.
Proposition 2. The LSIโs optimal reservation quantity, ๐โ๐๐๐ , is
affected by coefficients ๐ผ and ๐พ. For any ๐ผ > 0 and ๐พ > 0,one has the following: (a) ๐โ
๐๐๐ is decreasing in ๐ผ; (b) ๐โ
๐๐๐ is
decreasing in ๐พ; and (c) ๐โ๐๐๐ < ๐โ๐๐๐< ๐โ๐๐๐.
The proof of Proposition 2 is provided in Appendix. Themeaning of Proposition 2 is explained as follows. (a) TheLSIโs actual decision is affected by his inequity-averse degreeif he suffers from disadvantageous inequality. That is, ifthe LSI behaves more spitefully (the averse degree towardsdisadvantageous inequality is high), his reservation quantitywill further deviate from ๐
โ
cen to punish the FLSP. (b) TheLSIโs reservation quantity decreases with the increase of ๐พwhen a neutral FLSP sells some kinds of logistics services toa spiteful LSI. In other words, the higher the spiteful LSIโsperceived relative advantage against the FLSP is, the lessthe quantity of logistics service he will book. (c) If the LSIsuffers fromdisadvantageous inequality, his spiteful effectwilldiscourage him from making greater efforts on reservation,and his reservation quantity is smaller than the centralizedreservation quantity.
Proposition 3. The LSIโs optimal reservation quantity, ๐โ๐๐๐ , is
related to his procurement cost ๐๐and shortage cost ๐
๐ and the
FLSPโs operation cost ๐๐; that is, (a) ๐โ
๐๐๐ is decreasing in ๐
๐; (b)
๐โ๐๐๐
is increasing in ๐๐ ; and (c) ๐โ
๐๐๐ is increasing in ๐
๐.
The proof of Proposition 3 is provided in Appendix.Proposition 3 indicates that when the LSI suffers from dis-advantageous inequality, his optimal reservation quantity isrelated not only to his procurement cost and shortage costbut also to the FLSPโs operation cost. Specifically, with theincrease of the procurement cost, the LSI will decrease hisreservation quantity to avoid paying more procurement cost.With the increase of the shortage cost, the LSI will increase
his reservation quantity to avoid capacity shortage. With theincrease of the FLSPโs operation cost, the LSI will increasehis reservation quantity to seek a more fair trade. It can beseen from (8) that the fair-neutral LSIโs reservation quantityis only affected by his procurement cost and shortage cost,while the spiteful LSIโs reservation quantity is also affectedby the FLSPโs operation cost. This just reflects the natureof fairness concerns; that is, the LSI cares not only abouthis own profit but also about the FLSPโs profit. Combin-ing with Proposition 2, we observe that the LSIโs spitefuleffect is restrained by the increase of the FLSPโs operationcost.
Proposition 4. If the LSI suffers from disadvantageousinequality, one has the following: (a) ฮ ๐๐๐
๐ผ, ฮ ๐๐๐ ๐น, and ฮ ๐๐๐
๐ฟare
all decreasing in ๐ผ; (b)ฮ ๐๐๐ ๐ผ,ฮ ๐๐๐ ๐น, andฮ ๐๐๐
๐ฟare all decreasing in
๐พ.
The proof of Proposition 4 is provided in Appendix. Themeaning of Proposition 4 is as follows: (a) profits of theLSI, the FLSP, and the entire LSSC all decrease as the LSIโsinequity-averse degree increases; that is, the spiteful effectalways leads to the reduction of the LSSCโs performance.(b) The higher the LSIโs perceived relative advantage againstthe FLSP is, the less the profits of the participants and theentire LSSC will be obtained. This is common in reality.For example, if a company feels unfairly treated in thecooperation with his partner, he will behave spitefully tohis partner. The bigger his contribution to the channel is,the tougher his sanction to his partner will be. That is,the company will decrease his reservation quantity evenif his own interest will be hurt, and the partner will bedissatisfied with the collaboration. Sometimes, the partnerwill counterattack the companyโs punishment. This will leadto further deterioration of the partnership and reduction ofthe LSSCโs performance.
Proposition 5. If the LSI suffers from disadvantageousinequality, then one has the following: (a) ฮ ๐๐๐
๐ผ< ฮ ๐๐๐๐ผ
, ฮ ๐๐๐ ๐น<
ฮ ๐๐๐๐น
, and ฮ ๐๐๐ ๐ฟ< ฮ ๐๐๐๐ฟ
; (b) channel coordination of the LSSCcannot be achieved.
The proof of Proposition 5 is provided in Appendix.Proposition 5 shows that the optimal profit of the LSSCcannot be achieved through a simple reservation price-onlycontract if the LSI suffers from disadvantageous inequality,and the coordination effect is affected by the LSIโs fairnessconcerns in the decentralized setting. That is, the doublemarginalization problem becomes worse if the LSI suffersfrom disadvantageous inequality.
6 Mathematical Problems in Engineering
3.2.2. Advantageous Inequality. When the LSI accepts theFLSPโs reservation price-only contract and his payoff is largerthan ๐พ times that of the FLSPโs outcome, the LSI will reserve
enough logistics service capacity to maximize his utility.According to (6), (7), and (9), the optimization problem facedby the LSI under advantageous inequality can be defined as
max๐โฅ0
๐๐ผ
adv = (1 โ ๐ฝ)ฮ ๐ผ + ๐ฝ๐พฮ ๐น
= (1 โ ๐ฝ) [๐๐ โ ๐โซ๐
0
๐น (๐ฅ) ๐๐ฅ โ (๐ค + ๐๐) ๐ โ ๐๐
๐ + ๐๐ ๐ โ ๐๐ โซ๐
0
๐น (๐ฅ) ๐๐ฅ] + ๐ฝ๐พ (๐ค โ ๐๐) ๐.
(12)
By (12), we can get the following propositions.
Proposition 6. If the LSI experiences advantageous inequalityunder the reservation price-only contract, the optimal reserva-tion quantity, ๐โ
๐๐V, is
๐โ
๐๐V = ๐นโ1
(1 โ(1 โ ๐ฝ) (๐ค + ๐
๐) โ ๐ฝ๐พ (๐ค โ ๐
๐)
(1 โ ๐ฝ) (๐ + ๐๐ )
) . (13)
The proof of Proposition 6 is provided in Appendix.Proposition 6 indicates that the LSIโs expected utility, ๐๐ผadv, isstrictly concave with respect to ๐. That is to say, when the LSIaccepts the reservation price-only contract and experiencesadvantageous inequality, his optimal reservation quantity is๐โ
adv.
Proposition 7. The optimal reservation quantity, ๐โ๐๐V, is
affected by the coefficient ๐ฝ. For any ๐พ > 0, one has thefollowing: (a) ๐โ
๐๐V is increasing in ๐ฝ; (b) ๐โ
๐๐๐< ๐โ๐๐V < ๐
โ
๐๐๐
if 0 < ๐ฝ < 1/(1 + ๐พ); (c) ๐โ๐๐๐< ๐โ๐๐V = ๐
โ
๐๐๐if ๐ฝ = 1/(1 + ๐พ);
and (d) ๐โ๐๐๐< ๐โ๐๐๐< ๐โ๐๐V if 1/(1 + ๐พ) < ๐ฝ < 1.
The proof of Proposition 7 is provided in Appendix.Proposition 7 indicates that if the LSI experiences advanta-geous inequality, his reservation quantity, ๐โadv, will go up ashis inequity-averse degree increases. In other words, if the LSIis insufficiently averse to advantageous inequality, then ๐โadv <๐โcen; if the LSI is sufficiently averse to advantageous inequality(i.e., ๐ฝ = 1/(1 + ๐พ)), then ๐โadv = ๐
โ
cen; if the LSI is excessivelyaverse to advantageous inequality, then ๐โadv > ๐
โ
cen. Besides,in the decentralized setting, the reservation quantity of thegenerous LSI is bigger than that of the neutral LSI.
Proposition 8. The optimal reservation quantity, ๐โ๐๐V, is
affected by the coefficient ๐พ. For any 0 < ๐ฝ < 1, one has thefollowing: (a) ๐โ
๐๐V is increasing in ๐พ; (b) ๐โ
๐๐๐< ๐โ๐๐V < ๐
โ
๐๐๐if
0 < ๐พ < (1 โ ๐ฝ)/๐ฝ; (c) ๐โ๐๐๐< ๐โ๐๐V = ๐
โ
๐๐๐if ๐พ = (1 โ ๐ฝ)/๐ฝ; and
(d) ๐โ๐๐๐< ๐โ๐๐๐< ๐โ๐๐V if ๐พ > (1 โ ๐ฝ)/๐ฝ.
The proof of Proposition 8 is provided in Appendix.Proposition 8 indicates that the LSIโs reservation quantity,๐โadv, is increasing in ๐พwhen a neutral FLSP sells some kinds oflogistics service to a generous LSI. In other words, the greaterthe generous LSIโs perceived relative advantage against theFLSP is, the larger the quantity of logistics service he willreserve. When the LSIโs perceived relative advantage againstthe FLSP is satisfied with ๐พ = (1 โ ๐ฝ)/๐ฝ, his optimal bookingstrategy is the same as the one in the centralized setting.
Proposition 9. The LSIโs optimal reservation quantity, ๐โ๐๐V, is
related to his procurement cost ๐๐and shortage cost ๐
๐ and the
FLSPโs operation cost ๐๐; that is, (a) ๐โ
๐๐V is decreasing in ๐๐; (b)๐โ๐๐V is increasing in ๐๐ ; and (c) ๐
โ
๐๐V is decreasing in ๐๐.
The proof of Proposition 9 is provided in Appendix.Proposition 9 shows that a generous LSIโs reservation quan-tity is affected not only by his procurement cost and shortagecost but also by the FLSPโs operation cost. Specifically, theLSIโs reservation quantity will decrease as his procurementcost increases. With the increase of the shortage cost, theLSI will increase his reservation quantity to avoid capacityshortage. With the increase of FLSPโs operation cost, the LSIwill decrease his reservation quantity so as to seek a morefair trade. Combining with Proposition 7, we observe that theLSIโs generous effect will be restrained by the increase of theoperation cost.
Proposition 10. In the decentralized setting, when the LSIexperiences advantageous inequality, one has the following: (a)ฮ ๐๐V๐ผ
is decreasing in ๐ฝ, ฮ ๐๐V๐น
is increasing in ๐ฝ, and ฮ ๐๐V๐ฟ
isincreasing (decreasing) in ๐ฝ if ๐ฝ < 1/(1 + ๐พ) (๐ฝ > 1/(1 + ๐พ));(b) ฮ ๐๐V๐ผ
is decreasing in ๐พ, ฮ ๐๐V๐น
is increasing in ๐พ, and ฮ ๐๐V๐ฟ
isincreasing (decreasing) in ๐พ if ๐พ < (1 โ ๐ฝ)/๐ฝ (๐พ < (1 โ ๐ฝ)/๐ฝ).
The proof of Proposition 10 is provided in Appendix. Themeaning of Proposition 10 is as follows. (a) Profit allocationof the LSSC is affected by the LSIโs averse degree towardsadvantageous inequality (๐ฝ). With the increase of ๐ฝ, the LSIwill shift part of his monetary payoff to the FLSP, and theentire channel profit first experiences an increase and thenfollows a decline; that is, the LSIโs generous effect has animportant role to improve (reduce) the LSSCโs performancewhen ๐ฝ < ๐ฝ
1(๐ฝ > ๐ฝ
1). (b) Profit allocation of the LSSC is also
affected by the coefficient ๐พ, and the impact of ๐พ is the sameas ๐ฝ. That is, the bigger the LSIโs perceived relative advantageagainst the FLSP is, the more he will tend to shift his profit tothe FLSP.
Proposition 11. In the situation that the LSI experiencesadvantageous inequality, channel coordination in the LSSC canbe achieved if ๐ฝ = 1/(1 + ๐พ).
The proof of Proposition 11 is provided in Appendix.Proposition 11 shows that the reservation price-only contractcannot coordinate the entire channel in the LSSC when theLSI does not have fairness concerns or the LSI experiences
Mathematical Problems in Engineering 7
Table 1:The influences of coefficients ๐ผ, ๐ฝ, and ๐พ on the reservationquantities and the channel profits under disadvantageous andadvantageous inequality.
Coefficients Disadvantageous inequality Advantageous inequality๐โdis ฮ dis
๐ผฮ dis๐น
ฮ dis๐ฟ
๐โadv ฮ adv๐ผ
ฮ adv๐น
ฮ adv๐ฟ
๐ผ โ โ โ โ โ โ โ โ๐พ โ โ โ โ โ โ โ โโ
๐ฝ โ โ โ โ โ โ โ โโ
Note: โ and โ denote that the result is decreasing and increasing in ๐ผ, ๐ฝ, or๐พ, respectively, and โโ denotes that the result first goes up and then goesdown with the increase of ๐ผ, ๐ฝ, or ๐พ. โ denotes that ๐ผ, ๐ฝ, or ๐พ has no effecton the result.
disadvantageous inequality, but the contract can coordi-nate the entire channel under the certain condition (๐ฝ =
1/(1 + ๐พ)) when the LSI experiences advantageous inequal-ity.
Next we discuss the changes of profit and utility of thechannel members to achieve the above-mentioned channelcoordination. If ๐ฝ = 1/(1 + ๐พ), it can be seen fromPropositions 9 and 11 that the profit of a generous LSI inthe coordinated scenario is smaller than that of a neutralLSI in the decentralized setting (i.e., ฮ adv
๐ผ= ฮ cen๐ผ< ฮ dec๐ผ
),and the profits of the FLSP and the entire LSSC are greaterthan the ones in the traditional decentralized setting (i.e.,ฮ
adv๐น
= ฮ cen๐น
> ฮ dec๐น
and ฮ adv๐ฟ
= ฮ cen๐ฟ
> ฮ dec๐ฟ
).Thus, if the LSI experiences advantageous inequality, thereservation price-only contract is beneficial to both the FLSPand the entire LSSC, but unfavorable to the LSI. Motivatedby the concerns of fairness, the LSI will change his objective;that is, profit maximization objective will be changed intoutility maximization objective. When the LSI experiencesadvantageous inequality, his reservation quantity should be๐โ
adv so as to maximize his utility. Specially, if ๐ฝ = 1/(1 + ๐พ),the generous LSI can not only maximize his utility but alsomaximize the profit and the total utility of the entire channel;that is, the channel coordination can be achieved. Here, thetotal utility is the sum of the LSIโs utility and the FLSPโs profit(utility). Although the LSIโs profit in the coordinated situationis smaller than the one in the traditional decentralized setting,the LSI feels more fair; that is, the LSI tends to increasehis reservation quantity to avoid feeling more advantageousinequality.
Table 1 summarizes the impacts of the coefficients ๐ผ, ๐ฝ,and ๐พ on the LSIโs reservation quantity and the profits ofthe channel members in the LSSC under disadvantageousinequality and advantageous inequality. It can be seen fromTable 1 that the impacts of ๐ผ and ๐พ (๐ฝ and ๐พ) on the LSIโsdecision and the performance of the LSSC are the same if theLSI experiences disadvantageous inequality (advantageousinequality).
4. Numerical Examples
In this section, we give several numerical examples underboth disadvantageous and advantageous inequality to illus-trate the above theoretical results. For the purpose of our
numerical demonstration, we consider that the logisticsdemand in the market follows the normal distribution [18,35],๐ท โผ ๐(1000, 1002).
4.1. Relevant Numerical Examples under DisadvantageousInequality. In this subsection, we give two numerical exam-ples under disadvantageous inequality. One is to illustrate thechanges of the reservation quantities and the entire channelprofits with respect to ๐ผ and ๐พ. The other is to explore theimpacts of the procurement cost, the shortage cost, and theoperation cost on the reservation quantities and the channelmembersโ profits.
Example 1. In this example, to satisfy ๐๐ > ๐ค > ๐
๐> ๐๐and
ensure that the profit of the LSI is lower than his equitableprofit, we set the parameters as follows: ๐
๐= 4, ๐๐= 10, ๐ค =
18, ๐๐ = 22, and ๐ = 30.
Figure 1 presents the results about the impacts of ๐ผ and๐พ on the reservation quantities and the entire channel profitsunder disadvantageous inequality. Figure 1(a) shows that thereservation quantity of the spiteful LSI decreases as ๐ผ or๐พ increases. In the decentralized setting, the reservationquantity of the spiteful LSI is not greater than that of thefair-neutral LSI. In addition, the reservation quantity of boththe spiteful and the fair-neutral LSI in the decentralizedsetting is less than the centralized reservation quantity.Theseresults are in accordance with Proposition 2. Figure 1(b)shows that the entire channel profit is decreasing in ๐ผ or๐พ. In the decentralized setting, the entire channel profit ofthe disadvantageous inequality scenario is less than that ofthe fair-neutral scenario, and both of them are less thanthose of the centralized setting.The results show that channelcoordination of the LSSC cannot be achieved when the LSIsuffers from disadvantageous inequality. These results are inaccordance with Propositions 4 and 5.
Example 2. In this example, we set three cases to analyze theimpacts of ๐
๐, ๐๐ , and ๐
๐on the reservation quantities and the
channel membersโ profits under disadvantageous inequality.To satisfy ๐
๐ > ๐ค > ๐
๐> ๐๐and ensure that the profit of the
LSI is lower than his equitable profit, the parameters for thethree cases are set as follows.
Case 1. Consider ๐๐โ [2, 9], ๐ผ = 1, ๐พ = 1, ๐
๐= 10, ๐ค = 18,
๐๐ = 22, and ๐ = 30.
Case 2. Consider ๐๐ โ [18, 25], ๐ผ = 1, ๐พ = 1, ๐
๐= 4, ๐๐= 10,
๐ค = 18, and ๐ = 30.
Case 3. Consider ๐๐โ [5, 12], ๐ผ = 1, ๐พ = 1, ๐
๐= 4, ๐ค = 18,
๐๐ = 22, and ๐ = 30.For Case 1, the results are presented in Figure 2. In
Figure 2(a), we can observe that the reservation quantityof the spiteful LSI is decreasing in ๐
๐, and this result is in
accordance with Proposition 3. Figure 2(b) shows that whenthe LSI experiences disadvantageous inequality, the profit ofthe LSI and the FLSP will decrease with the increase of theLSIโs procurement cost.
8 Mathematical Problems in Engineering
0 0.2 0.4 0.6 0.8 1 1.2 1.4960
980
1000
1020
1040
1060
1080
qโ
qโcenqโdec
qโdis, ๐พ = 1.0
qโdis, ๐พ = 1.5
qโdis, ๐พ = 2.0
๐ผ
(a) The reservation quantities versus (๐ผ, ๐พ)
0 0.2 0.4 0.6 0.8 1 1.2 1.41.35
1.36
1.37
1.38
1.39
1.4
1.41
1.42
1.43
1.44
ฮ
๐ผ
ร104
ฮ cenL
ฮ decL
ฮ disL , ๐พ = 1.0
ฮ disL , ๐พ = 1.5
ฮ disL , ๐พ = 2.0
(b) The entire channel profits versus (๐ผ, ๐พ)
Figure 1: Impacts of ๐ผ and ๐พ on the reservation quantities and the entire channel profits under disadvantageous inequality.
2 3 4 5 6 7 8 9960
980
1000
1020
1040
1060
1080
1100
qโ
cm
qโdisqโcen
qโdec
(a) The reservation quantities versus ๐๐
2 3 4 5 6 7 8 90
1000
2000
3000
4000
5000
6000
7000
8000
9000
ฮ
cm
ฮ disI
ฮ disF
ฮ decI
ฮ decF
(b) The channel membersโ profits versus ๐๐
Figure 2: Impacts of ๐๐on the reservation quantities and the channel membersโ profits under disadvantageous inequality.
For Case 2, the results are shown in Figure 3. Figure 3(a)shows that the reservation quantity of the spiteful LSI willincrease as the shortage cost increases, and this result is inaccordance with Proposition 3. Figure 3(b) shows that whenthe LSI experiences disadvantageous inequality, his profit willdecrease as the shortage cost increases, while the FLSPโs profitwill increase.
For Case 3, the results are presented in Figure 4.Figure 4(a) demonstrates that the reservation quantity of thespiteful LSI is affected by the FLSPโs operation cost, and itwill increase as the operation cost increases.The results are inaccordance with Proposition 3. Figure 4(b) shows that whenthe LSI suffers from disadvantageous inequality, his profit
will increase as the operation cost increases, while the FLSPโsprofit will decrease.
It can be seen from Figures 1(a), 2(a), and 3(a) that thereservation quantity of the spiteful LSI is always smallerthan that of the fair-neutral LSI in the decentralized set-ting, and the reservation quantities of the spiteful LSIand the fair-neutral LSI are both smaller than the cen-tralized reservation quantity. Moreover, from Figures 1(b),2(b), and 3(b), we can observe that the profit of both theLSI and the FLSP under fair-neutral scenario is smallerthan that in the disadvantageous inequality scenario. Thisreflects that the LSI tends to punish the FLSP so as to
Mathematical Problems in Engineering 9
18 19 20 21 22 23 24 25980
990
1000
1010
1020
1030
1040
1050
1060
1070
qโ
cs
qโdisqโcen
qโdec
(a) The reservation quantities versus ๐๐
18 19 20 21 22 23 24 255500
6000
6500
7000
7500
8000
8500
ฮ
cs
ฮ disI
ฮ disF
ฮ decI
ฮ decF
(b) The channel membersโ profits versus ๐๐
Figure 3: Impacts of ๐๐ on the reservation quantities and the channel membersโ profits under disadvantageous inequality.
5 6 7 8 9 10 11 12980
1000
1020
1040
1060
1080
1100
qโ
co
qโdis
qโcen
qโdec
(a) The reservation quantities versus ๐๐
5 6 7 8 9 10 11 125000
6000
7000
8000
9000
10000
11000
12000
13000
14000
ฮ
co
ฮ disI
ฮ disF
ฮ decI
ฮ decF
(b) The channel membersโ profits versus ๐๐
Figure 4: Impacts of ๐๐on the reservation quantities and the channel membersโ profits under disadvantageous inequality.
seek a more fair trade even if his own profit will behurt.
4.2. Relevant Numerical Examples under AdvantageousInequality. In this subsection, we give two numericalexamples under advantageous inequality. One is to observethe change of the reservation quantities and the entirechannel profit with respect to ๐ฝ and ๐พ. The other is to explorethe impacts of the procurement cost, the operation cost,and the shortage cost on the reservation quantities and thechannel membersโ profits.
Example 3. In this example, to satisfy ๐๐ > ๐ค > ๐
๐> ๐๐and
ensure that the profit of the LSI is larger than his equitableprofit, we specify the parameters as follows: ๐
๐= 4, ๐๐= 14,
๐ค = 16, ๐๐ = 22, and ๐ = 30.
Figure 5 shows the results of the impacts of ๐ฝ and ๐พ onthe reservation quantities and the entire channel profits underadvantageous inequality. Figure 5(a) shows that a generousLSIโs reservation quantity will increase as ๐ฝ or ๐พ increases,and when ๐ฝ = 1/(1 + ๐พ) (e.g., ๐ฝ = 0.5, ๐พ = 1), the LSIโsreservation quantity is equal to the centralized reservation
10 Mathematical Problems in Engineering
0 0.1 0.2 0.3 0.4 0.5 0.61020
1025
1030
1035
1040
1045
1050
1055
1060
1065
qโ
๐ฝ
qโcen
qโdec
qโadv, ๐พ = 1.0
qโadv, ๐พ = 1.5
qโadv, ๐พ = 2.0
(a) The reservation quantities versus (๐ฝ, ๐พ)
0 0.1 0.2 0.3 0.4 0.5 0.61.003
1.004
1.005
1.006
1.007
1.008
1.009
ฮ
ฮ cenL
ฮ decL
ฮ advL , ๐พ = 1.0 ฮ adv
L , ๐พ = 1.5
ฮ advL , ๐พ = 2.0
๐ฝ
ร104
(b) The entire channel profits versus (๐ฝ, ๐พ)
Figure 5: Impacts of ๐ฝ and ๐พ on the reservation quantities and the entire channel profits under advantageous inequality.
1 1.5 2 2.5 3 3.5 41030
1040
1050
1060
1070
1080
1090
qโ
cm
qโcen
qโadv
qโdec
(a) The reservation quantity versus ๐๐
1 1.5 2 2.5 3 3.5 44000
5000
6000
7000
8000
9000
10000
11000
12000
13000
ฮ
cm
ฮ advI
ฮ advF
ฮ decI
ฮ decF
(b) The channel membersโ profits versus ๐๐
Figure 6: Impacts of ๐๐on the reservation quantities and the channel membersโ profits under advantageous inequality.
quantity. The results are in accordance with Propositions 7and 8. Figure 5(b) shows that the entire channel profit firstincreases and then decreases, with the increase of ๐ฝ. Also,there is the same conclusion for ๐พ. When ๐ฝ = 1/(1 โ ๐พ)
(e.g., ๐ฝ = 0.4, ๐พ = 1.5), the entire channel profit underadvantageous inequality is equal to the entire channel profitin the centralized setting; that is, the channel coordinationin the LSSC can be achieved. Obviously, the results are inaccordance with Propositions 9 and 11.
Example 4. In this example, we set three cases to investigatethe impacts of ๐
๐, ๐๐ , and ๐
๐on the reservation quantities and
channel membersโ profits under advantageous inequality. Tosatisfy ๐
๐ > ๐ค > ๐
๐> ๐๐and ensure that the profit of the LSI is
larger than his equitable profit, we set the parameters for thethree cases as follows.
Case 1. One has ๐๐โ [1, 4], ๐ฝ = 0.5, ๐พ = 1, ๐
๐= 10, ๐ค = 15,
๐๐ = 22, and ๐ = 30.
Case 2. One has ๐๐ โ [18, 25], ๐ฝ = 0.5, ๐พ = 1, ๐
๐= 4, ๐๐= 10,
๐ค = 15, and ๐ = 30.
Case 3. One has ๐๐โ [8, 14], ๐ฝ = 0.5, ๐พ = 1, ๐
๐= 4, ๐ค = 15,
๐๐ = 22, and ๐ = 30.For Case 1, the results are shown in Figure 6. From
Figure 6(a), we can find that the reservation quantity of agenerous LSI will decrease as the procurement cost increases.
Mathematical Problems in Engineering 11
18 19 20 21 22 23 24 251025
1030
1035
1040
1045
1050
1055
1060
1065
1070
qโ
qโcenqโadv
qโdec
cs
(a) The reservation quantities versus ๐๐
18 19 20 21 22 23 24 254000
5000
6000
7000
8000
9000
10000
ฮ
ฮ advI
ฮ advF
ฮ decI
ฮ decF
cs
(b) The channel membersโ profits versus ๐๐
Figure 7: Impacts of ๐๐ on the reservation quantities and the channel membersโ profits under advantageous inequality.
8 9 10 11 12 13 141030
1035
1040
1045
1050
1055
1060
1065
1070
1075
qโ
qโcen
qโadv
qโdec
co
(a) The reservation quantities versus ๐๐
8 9 10 11 12 13 141000
2000
3000
4000
5000
6000
7000
8000
9000
10000
ฮ
ฮ advI
ฮ advF
ฮ decI
ฮ decF
co
(b) The channel membersโ profits versus ๐๐
Figure 8: Impacts of ๐๐on the reservation quantities and the channel membersโ profits under advantageous inequality.
Apparently, the results are in accordance with Proposition 9.Figure 6(b) shows that when the LSI experiences advanta-geous inequality, the profit of the LSI and the FLSP willdecrease with the increase of the procurement cost.
For Case 2, the results are illustrated in Figure 7.Figure 7(a) shows that the reservation quantity of a generousLSI will increase as the shortage cost increases, and this resultis in accordance with Proposition 9. Figure 7(b) shows thatwhen the LSI experiences advantageous inequality, his profitwill decrease with the increase of the shortage cost, while theFLSPโs profit will increase.
For Case 3, the results are presented in Figure 8.Figure 8(a) shows that the reservation quantity of a generousLSI is affected by the FLSPโs operation cost, and it is decreas-ing in ๐
๐. The results are in accordance with Proposition 9.
Figure 8(b) demonstrates that when the LSI experiencesadvantageous inequality, the LSIโs profit will increase as theoperation cost increases, while the FLSPโs profit will decrease.
In addition, we can conclude from Figures 6(a), 7(a),and 8(a) that the reservation quantity in the advantageousinequality scenario is equal to the centralized reservation
12 Mathematical Problems in Engineering
quantity in the situation of ๐ฝ = 1/(1 + ๐พ). This indicates thatthe coordination condition is not affected by the procurementcost, the shortage cost, or the operation cost. Also, it can beseen from Figures 6(b), 7(b), and 8(b) that the LSIโs profit inthe fair scenario is always smaller than that in the fair-neutralscenario, while for the FLSP, the conclusion is opposite. Thisindicates that if the LSI experiences advantageous inequality,he tends to reward the FLSP at the cost of decreasing his ownprofit so as to seek a more fair trade.
5. Conclusions
In this paper, fairness concerns are introduced into theanalysis of channel coordination problem in a two-stageLSSC. Given the LSIโs procurement cost and shortage cost,the FLSPโs operation cost, and stochastic market demand, themodels for a reservation price-only contract are establishedunder disadvantageous inequality and advantageous inequal-ity. The impacts of fairness concerns and the related costson channel performance (i.e., the LSIโs reservation quantityand channel profit) and channel coordination are analyzed.Compared with the existing literatures, the novelties of thepaper are summarized in two aspects: one is that we capturethe fairness factor in the collaborative cooperation betweenthe logistics enterprises so as to get some new managerialinsights to guide the practice; the other one is thatwe considera more comprehensive situation when carrying out ourfairness research; that is, the procurement cost, the potentialshortage cost, and the salvage value are considered understochastic market demand so as to lead the managers to takebetter decisions.
We find that channel coordination cannot be achievedby a simple reservation price-only contract in a fair-neutralscenario (i.e., both the LSI and the FLSP are fair-neutral)as well as in the situation that the LSI suffers from dis-advantageous inequality, while channel coordination canbe achieved under certain condition (see Proposition 11) ifthe LSI experiences advantageous inequality. This meansthat the double marginalization problem can be alleviatedby the LSIโs generosity. Our study also shows that, in thedecentralized setting, the LSIโs spite for disadvantageousinequality will result in less reservation quantity, while theLSIโs generosity for advantageous inequality will result ingreater reservation quantity. Meanwhile, the LSIโs perceivedrelative advantage against the FLSP also plays an importantrole in alleviating (aggravating) the double marginalizationproblem and improving (worsening) the channel perfor-mance. Furthermore, another interesting finding shows thatthe LSIโs reservation quantity is affected not only by hisprocurement cost and shortage cost but also by the FLSPโsoperation cost when the LSI perceives either disadvantageousor advantageous inequality.This just reflects that the LSI caresnot only about his own profit but also about the FLSPโs profit.
However, our study has some limitations, which mayserve as directions for future research. First, in our study, thechannel can be coordinated by the simple reservation price-only contract under certain condition, but the conditionrarely exists in reality. Hence, given fairness concerns, itseems interesting to find out some desirable contracts from
multiple different contracts such as the buyback contractand the revenue-sharing contract. Second, we assume thatthe channel members have full information, which seemsa strong assumption in reality [27]. Under the situation ofinformation asymmetry, the channel coordination problemin the LSSC is a noteworthy research work. Last, we just studythe channel coordination problem under the simple channelstructure, that is, the LSSC composed of one LSI and oneFLSP. It is necessary to further investigate the channel coordi-nation problem under other complicated channel structuressuch as one LSI and two FLSPs.
Appendix
Proof of Proposition 1. By (10), we can obtain
๐๐๐ผdis๐๐
= (1 + ๐ผ) ฮ โ ๐ผ๐พ (๐ค โ ๐๐) ,
๐2๐๐ผdis๐๐2
= โ (1 + ๐ผ) (๐ + ๐๐ ) ๐ (๐) ,
(A.1)
where ฮ = (๐+ ๐๐ )[1 โ๐น(๐)] โ (๐ค+ ๐
๐). Because ๐(๐) > 0, we
can get ๐2๐๐ผdis/๐๐2 < 0, so ๐๐ผdis is a strictly concave function
of ๐. Let ๐๐๐ผdis/๐๐ = 0; we can obtain the optimal reservationquantity determined by (11).
Proof of Proposition 2. (a) By (11), we can get
๐๐โdis๐๐ผ
=๐๐นโ1
๐๐ธ
๐๐ธ
๐๐ผ= โ๐๐นโ1
๐๐ธ
๐พ (๐ค โ ๐๐)
(1 + ๐ผ)2
(๐ + ๐๐ ), (A.2)
where
๐ธ = 1 โ(1 + ๐ผ) (๐ค + ๐
๐) + ๐ผ๐พ (๐ค โ ๐
๐)
(1 + ๐ผ) (๐ + ๐๐ )
. (A.3)
Since ๐น(๐ฅ) and ๐นโ1(๐ฅ) are monotonically increasing and ๐ค >๐๐, we have ๐๐โdis/๐๐ผ < 0; that is, ๐
โ
dis is decreasing in ๐ผ.(b) Similarly, by (11), we can get
๐๐โdis๐๐พ
=๐๐นโ1
๐๐ธ
๐๐ธ
๐๐พ= โ๐๐นโ1
๐๐ธ
๐ผ (๐ค โ ๐๐)
(1 + ๐ผ) (๐ + ๐๐ )< 0; (A.4)
that is, ๐โdis is decreasing in ๐พ.(c) Since ๐ผ > 0, ๐พ > 0, and ๐ค > ๐
๐, it is known from (8)
and (11) that
1 โ๐ค + ๐๐
๐ + ๐๐
> 1 โ(1 + ๐ผ) (๐ค + ๐
๐) + ๐ผ๐พ (๐ค โ ๐
๐)
(1 + ๐ผ) (๐ + ๐๐ )
. (A.5)
Since ๐นโ1(๐ฅ) is monotonically increasing, we can get ๐โdis <๐โdec. Above all, we have ๐
โ
dis < ๐โ
dec < ๐โ
cen. Thus, the proposi-tion is proved.
Mathematical Problems in Engineering 13
Proof of Proposition 3. By (11), we can get
๐๐โdis๐๐๐
=๐๐นโ1
๐๐ธ
๐๐ธ
๐๐๐
= โ๐๐นโ1
๐๐ธ
1
๐ + ๐๐
< 0,
๐๐โdis๐๐๐
=๐๐นโ1
๐๐ธ
๐๐ธ
๐๐๐
=๐๐นโ1
๐๐ธ
(1 + ๐ผ) (๐ค + ๐๐) + ๐ผ๐พ (๐ค โ ๐
๐)
(1 + ๐ผ) (๐ + ๐๐ )2
> 0,
๐๐โdis๐๐๐
=๐๐นโ1
๐๐ธ
๐๐ธ
๐๐๐
=๐๐นโ1
๐๐ธ
๐ผ๐พ
(1 + ๐ผ) (๐ + ๐๐ )> 0,
(A.6)
where
๐ธ = 1 โ(1 + ๐ผ) (๐ค + ๐
๐) + ๐ผ๐พ (๐ค โ ๐
๐)
(1 + ๐ผ) (๐ + ๐๐ )
. (A.7)
It is concluded by the above formulas that Proposition 3holds.
Proof of Proposition 4. Substituting ๐โdis determined by (11)into (3), (6), and (7) and taking the first derivative withrespect to ๐ผ and ๐พ, respectively, we can get
๐ฮ dis๐ผ
๐๐ผ= ๐๐๐โ
dis๐๐ผ,
๐ฮ dis๐น
๐๐ผ= ๐๐๐โ
dis๐๐ผ,
๐ฮ dis๐ฟ
๐๐ผ= ๐ ๐๐โ
dis๐๐ผ,
๐ฮ dis๐ผ
๐๐พ= ๐๐๐โ
dis๐๐พ,
๐ฮ dis๐น
๐๐พ= ๐๐๐โ
dis๐๐พ,
๐ฮ dis๐ฟ
๐๐พ= ๐ ๐๐โ
dis๐๐พ,
(A.8)
where ๐ = (๐ + ๐๐ )[1 โ ๐น(๐โdis)] โ (๐ค + ๐๐), ๐ = ๐ค โ ๐๐, and
๐ = (๐+๐๐ )[1โ๐น(๐โdis)]โ(๐๐+๐๐). According to Proposition 3,
we know that ๐โdis < ๐โ
dec < ๐โ
cen. By ๐โ
dis < ๐โ
dec and (8) and(11), we can get 1 โ ๐น(๐โdis) > (๐ค + ๐๐)/(๐ + ๐๐ ). By the aboveexpression of ๐, we can get ๐ > 0. Since ๐ค > ๐
๐, we know that
๐ > 0. By ๐โdis < ๐โ
cen and (4) and (11), we can get 1 โ ๐น(๐โdis) >(๐๐+๐๐)/(๐+๐
๐ ). By the above expression of ๐ , we can get ๐ > 0.
According to the proof process of Proposition 2,we know that๐๐โdis/๐๐ผ < 0; thuswe can get ๐ฮ
dis๐ผ/๐๐ผ < 0, ๐ฮ dis
๐น/๐๐ผ < 0, and
๐ฮ dis๐ฟ/๐๐ผ < 0 if ๐ > 0, ๐ > 0, and ๐ > 0. Similarly, we can also
obtain ๐ฮ dis๐ผ/๐๐พ < 0, ๐ฮ dis
๐น/๐๐พ < 0, and ๐ฮ dis
๐ฟ/๐๐พ < 0. Hence,
Proposition 4 holds.
Proof of Proposition 5. (a) By Section 3.1, we know that ฮ ๐ผis
concave with respect to ๐ and ๐โdec is the optimal solution, and
ฮ ๐นis increasing in ๐. By Proposition 2, we know that ๐โdis <
๐โdec. Substituting ๐โ
dis and ๐โ
dec into (6) and (7), respectively,we can get ฮ dis
๐ผ< ฮ dec๐ผ
and ฮ dis๐น< ฮ dec๐น
, respectively. Sinceฮ dis๐ฟ= ฮ dis๐ผ+ ฮ dis๐น
and ฮ dec๐ฟ= ฮ dec๐ผ+ ฮ dec๐น
, we can get ฮ dis๐ฟ<
ฮ dec๐ฟ
.(b) By Section 3.1, we know that ฮ
๐ฟis concave with
respect to ๐ and ๐โcen is the optimal solution. By Proposition 3,we know that ๐โdis < ๐โcen. Substituting ๐
โ
dis and ๐โcen into(3), respectively, we can get the correspondingฮ dis
๐ฟandฮ cen
๐ฟ.
Thus, we can get ฮ dis๐ฟ< ฮ cen๐ฟ
because ๐โdis < ๐โ
cen. This meansthat channel coordination of the LSSC cannot be achieved.In other words, when channel coordination in the LSSC isrealized, ๐ค = ๐
๐can be obtained by solving the equation
๐โdis = ๐โ
cen. In this case, the FLSPโs profit will be zero. Yetthis is inconsistent with the reality. Therefore, Proposition 5holds.
Proof of Proposition 6. By (12), we can get
๐๐๐ผadv๐๐
= (1 โ ๐ฝ) ฮ + ๐ฝ๐พ (๐ค โ ๐๐) ,
๐2๐๐ผadv๐๐2
= โ (1 โ ๐ฝ) (๐ + ๐๐ ) ๐ (๐) ,
(A.9)
whereฮ = (๐+๐๐ )[1โ๐น(๐)]โ(๐ค+๐
๐). Since๐(๐) > 0, we know
that ๐2๐๐ผadv/๐๐2 < 0. So๐๐ผadv is a strictly concave function of ๐.
Letting ๐๐๐ผadv/๐๐ = 0, we can obtain the optimal reservationquantity determined by (13).
Proof of Proposition 7. (a) By (12), we can get
๐๐โ
adv๐๐ฝ
=๐๐นโ1
๐๐ป
๐๐ป
๐๐ฝ=๐๐นโ1
๐๐ป
๐พ (๐ค โ ๐๐)
(1 โ ๐ฝ)2
(๐ + ๐๐ ), (A.10)
where
๐ป = 1 โ(1 โ ๐ฝ) (๐ค + ๐
๐) โ ๐ฝ๐พ (๐ค โ ๐
๐)
(1 โ ๐ฝ) (๐ + ๐๐ )
. (A.11)
Since ๐น(๐ฅ) and ๐นโ1(๐ฅ) are monotonically increasing and ๐ค >๐๐, we have ๐๐โadv/๐๐ฝ > 0; that is, ๐
โ
adv is increasing in ๐ฝ.(b) By (8) and (12), we know that ๐โadv = ๐
โ
dec if ๐ฝ = 0.Since ๐โadv is increasing in ๐ฝ, we know that ๐โdec < ๐
โ
adv if 0 <๐ฝ < 1. Further, by (4) and (12), we know that ๐โadv = ๐
โ
cen if๐ฝ = 1/(1 + ๐พ). Thus, ๐โadv < ๐
โ
cen if 0 < ๐ฝ < 1/(1 + ๐พ). Aboveall, we can get ๐โdec < ๐
โ
adv < ๐โ
cen if 0 < ๐ฝ < 1/(1 + ๐พ).(c) According to the proof process of (b), we know that
๐โ
dec < ๐โ
adv = ๐โ
cen if ๐ฝ = 1/(1 + ๐พ).(d) Similarly, we know that ๐โadv > ๐
โ
cen > ๐โ
dec if 1/(1+๐พ) <๐ฝ < 1. Therefore, the proposition is proved.
Proof of Proposition 8. Theproof of Proposition 8 is similar tothat of Proposition 7 and thus omitted.
14 Mathematical Problems in Engineering
Proof of Proposition 9. By (13), we can get
๐๐โadv๐๐๐
=๐๐นโ1
๐๐ป
๐๐ป
๐๐๐
= โ๐๐นโ1
๐๐ป
1
๐ + ๐๐
< 0,
๐๐โadv๐๐๐
= โ๐2๐๐ผ/๐๐๐๐๐
๐2๐๐ผ/๐๐2
=1 โ ๐น (๐)
(๐ + ๐๐ ) ๐ (๐)
> 0,
๐๐โadv๐๐๐
=๐๐นโ1
๐๐ป
๐๐ป
๐๐๐
= โ๐๐นโ1
๐๐ป
๐ฝ๐พ
(1 โ ๐ฝ) (๐ + ๐๐ )< 0,
(A.12)
where
๐ป = 1 โ(1 โ ๐ฝ) (๐ค + ๐
๐) โ ๐ฝ๐พ (๐ค โ ๐
๐)
(1 โ ๐ฝ) (๐ + ๐๐ )
. (A.13)
Hence, Proposition 9 holds.
Proof of Proposition 10. We substitute ๐โadv determined by (13)into (3), (6), and (7) and take the first derivative ofฮ adv
๐ฟ,ฮ adv๐ผ
,and ฮ adv
๐นwith respect to ๐ฝ and ๐พ, respectively. Thus, we can
get
๐ฮ adv๐ฟ
๐๐ฝ= ๐ ๐๐โ
adv๐๐ฝ
,
๐ฮ adv๐ผ
๐๐ฝ= ๐๐๐โ
adv๐๐ฝ
,
๐ฮ adv๐น
๐๐ฝ= ๐๐๐โ
adv๐๐ฝ
,
๐ฮ adv๐ฟ
๐๐พ= ๐ ๐๐โ
adv๐๐พ
,
๐ฮ adv๐ผ
๐๐พ= ๐๐๐โ
adv๐๐พ
,
๐ฮ adv๐น
๐๐พ= ๐๐๐โ
adv๐๐พ
,
(A.14)
where ๐ = (๐+ ๐๐ )[1 โ๐น(๐โadv)] โ (๐ค+ ๐๐), ๐ = ๐คโ ๐๐ > 0, and
๐ = (๐+๐๐ )[1โ๐น(๐โadv)]โ(๐๐+๐๐). By Proposition 7, we know
that ๐โadv > ๐โ
dec. Thus, according to (8) and (13), we can get1 โ ๐น(๐โadv) < (๐ค + ๐๐)/(๐ + ๐๐ ). According to this inequation,we can get ๐ < 0. By Proposition 7, we know that ๐โadv < ๐
โ
cenif 0 < ๐ฝ < 1/(1+ ๐พ) and ๐โadv > ๐
โ
cen if 1/(1+ ๐พ) < ๐ฝ < 1. Thus,from (4) and (13), we can get 1 โ ๐น(๐โadv) > (๐๐ + ๐๐)/(๐ + ๐๐ )if 0 < ๐ฝ < 1/(1 + ๐พ) and 1 โ ๐น(๐โadv) < (๐๐ + ๐๐)/(๐ + ๐๐ ) if1/(1+๐พ) < ๐ฝ < 1. According to these two inequations, we canget ๐ > 0 (๐ < 0) if 0 < ๐ฝ < 1/(1+๐พ) (1/(1+๐พ) < ๐ฝ < 1). By theproof process of Proposition 7, we know that ๐๐โadv/๐๐ฝ > 0.Thus, we can, respectively, get ๐ฮ adv
๐ผ/๐๐ฝ < 0, ๐ฮ adv
๐น/๐๐ฝ > 0,
and ๐ฮ adv๐ฟ/๐๐ฝ > 0 if 0 < ๐ฝ < 1/(1 + ๐พ) and ๐ฮ adv
๐ฟ/๐๐ฝ < 0
if 1/(1 + ๐พ) < ๐ฝ < 1. Similarly, we also can, respectively, get๐ฮ adv๐ผ/๐๐พ < 0, ๐ฮ adv
๐น/๐๐พ > 0, and ๐ฮ adv
๐ฟ/๐๐พ > 0 if 0 < ๐พ <
(1 โ ๐ฝ)/๐ฝ and ๐ฮ adv๐ฟ/๐๐พ < 0 if ๐พ > (1 โ ๐ฝ)/๐ฝ. This completes
the proof of Proposition 10.
Proof of Proposition 11. By Section 3.1, we know that ฮ ๐ฟis
concave with respect to ๐. By Proposition 7, we know that๐โ
adv = ๐โ
cen if ๐ฝ = 1/(1 + ๐พ). Substituting ๐โcen determinedby (4) and ๐โadv determined by (13) into (3), respectively, wecan get the correspondingฮ cen
๐ฟandฮ adv
๐ฟ. Thus, if ๐โadv = ๐
โ
cen,then we know ฮ adv
๐ฟ= ฮ cen๐ฟ
; that is, Proposition 11 holds.
Competing Interests
The authors declare that they have no competing interests.
Acknowledgments
This work was partly supported by the National Natural Sci-ence Foundation of China (Projects nos. 71271051, 71571039,and 71201020) and the Fundamental Research Funds for theCentral Universities, NEU, China (Projects nos. N140607001,N140604003, and N150606001).
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