Logistics Service Integrator Research Articles

How the LSSC networks affect the growth of logistics service integrator

According to different types of resources the logistics service integrator (LSI) acquires from the logistics service supply chain (LSSC) network, the LSSC networks can be divided into five sub-networks: social networks, logistics innovation networks, logistics collaboration networks, marketing networks and reputation networks. This study examines the relationships among five LSSC sub-networks and the influence of LSSC networks to the LSI performance by empirical method. The result shows that the developing of social networks, logistics innovation networks and marketing networks have an significant impact on the growth of LSI; reputational networks have an indirect impact on the firm growth by means of marketing networks; and up to now, the development of logistics collaboration networks are not very good, so it has little impact on the growth performance of LSI.

The impacts of logistics service integrator's overconfidence behaviour on supply chain decision under demand surge

This paper studies a two-echelon logistics service supply chain (LSSC) composed of one logistics service integrator (LSI) and one functional logistics service provider (FLSP). We develop a two-period service capacity procurement model where market demand surges in the second period. The LSI, as the Stackelberg game leader, tends to be overconfident when market demand surges. The results show that when the demand surges in the second period, if the overconfident purchasing capacity of LSI cannot meet the market demand, the overconfidence behaviour will negatively affect LSI's optimal pricing. Besides, the overconfidence behaviour leads to the lowest service level of the FLSP in the second period under demand surge. However, such negative impacts can be reduced or even eliminated in certain conditions through the FLSP-led mechanism and the dynamic wholesale price mechanism. The numerical simulation and the case study from China are used to illustrate the model and draw some conclusions. [Received 17 August 2017; Revised 19 February 2018; Accepted 30 March 2018]

The impacts of logistics service integrator's overconfidence behaviour on supply chain decision under demand surge

This paper studies a two-echelon logistics service supply chain (LSSC) composed of one logistics service integrator (LSI) and one functional logistics service provider (FLSP). We develop a two-period service capacity procurement model where market demand surges in the second period. The LSI, as the Stackelberg game leader, tends to be overconfident when market demand surges. The results show that when the demand surges in the second period, if the overconfident purchasing capacity of LSI cannot meet the market demand, the overconfidence behaviour will negatively affect LSI's optimal pricing. Besides, the overconfidence behaviour leads to the lowest service level of the FLSP in the second period under demand surge. However, such negative impacts can be reduced or even eliminated in certain conditions through the FLSP-led mechanism and the dynamic wholesale price mechanism. The numerical simulation and the case study from China are used to illustrate the model and draw some conclusions. [Received 17 August 2017; Revised 19 February 2018; Accepted 30 March 2018]

How does dynamic capability affect logistics service integrator's growth performance

For logistics service integrator (LSI), in a dynamic market, the only effective way for logistics enterprise obtaining greater benefits is to continue innovating and maintaining dynamic capabilities. In the use of sub-model multidimensional approach, we proposed that the dynamic capacity composed by the environmental awareness, resource integration capability and logistics flexibility capability. The paper gives the dynamic capability measure, the concept definition of LSI, how it affects the ability to build dynamic growth performance LSI growth models, and make an empirical analysis. It also finalise the structural model that dynamic capabilities impact on LSI growth performance. Then, we construct the model of the effect of dynamic capability on the growth performance of LSI. We deeply analyse mechanism of factors that affect growth merits of logistic service.

How the LSSC networks affect the growth of logistics service integrator

How the LSSC networks affect the growth of logistics service integrator

How does dynamic capability affect logistics service integrator's growth performance

How does dynamic capability affect logistics service integrator's growth performance

Capacity Procurement in Logistics Service Supply Chain with Demand Updating and Rational Expectation Behavior

This paper discusses the applicable conditions of two capacity procurement sub-strategies with two ordering opportunities, namely, sub-strategy I in which only increasing purchase quantity is allowed during the second ordering opportunity, and sub-strategy II in which either increasing or reducing order quantities is possible when the second order is placed. Our research is in the context of a logistics service supply chain (LSSC) consisted of a logistics service integrator (LSI) and a functional logistics service provider (FLSP). LSI purchases first a service capacity from FLSP long before demand is realized and then adjusts this ordering quantity based on demand updating. We developed the profit models for LSI and FLSP which also include the constraints of rational expectations. Based on the assumption of Bayesian updating, this paper investigates the conditions for sub-strategy II outperforming sub-strategy I. The main results are verified through numerical analysis. Counter-intuitively, sub-strategy II is not necessarily always better than sub-strategy I. When using sub-strategy II, LSI needs to purchase more service the first time of placing orders, but the expected profits increase for both LSI and FLSP only with certain conditions, which have been derived as propositions in this paper.

Decision model for the customer order decoupling point considering order insertion scheduling with capacity and time constraints in logistics service supply chain

In the context of mass customization logistics service, we explore how a new inserted order affects the logistics service integrator (LSIs) decision regarding the location of the customer order decoupling point (CODP). Considering a two-echelon logistics service supply chain (LSSC), consisting of an LSI and several functional logistics service providers (FLSPs), we establish a CODP decision model based on time scheduling with capacity and time constraints. The optimization objectives of the model include minimizing the average unit operation cost for the LSI and maximizing the average satisfaction of the FLSPs. In order to verify the viability of our model, with specific data derived from the daily scheduling operation records of the Baoyun Logistics Company, we perform a numerical analysis using genetic algorithms based on multiple datasets where a single parameter is changed each time while the other parameters remain unchanged. The results show that the CODP moves earlier with the increase of the volume of new order. Furthermore, as the new order's similarity coefficient increases or the new order's completion time requirement is relaxed, the CODP moves later in the LSSC. With a given similarity coefficient or time patience variance related to the new order, the maximum insertion volume decreases and the CODP moves later in the LSSC.

Decision method for the optimal number of logistics service providers with service quality guarantee and revenue fairness

This study investigates the problem that logistics service integrator (LSI) selects the optimal number of its functional logistics service providers (FLSPs) based on the service quality defect guarantee promised by FLSP and the revenue fairness concerns of LSI. This paper introduces a fairness entropy function to establish a new game model for determining the optimal number of FLSPs. Some conclusions about the impact of parameters on the optimal number of FLSPs are proposed with numerical analysis. For example, as the fairness constraints are satisfied, LSI prefers FLSPs who have higher level of business capacity which results a smaller number of FLSPs.

Order allocation of logistics service supply chain with fairness concern and demand updating: model analysis and empirical examination

Regarding a two-echelon supply chain consisting of a logistics service integrator (LSI) and several functional logistics service providers (FLSPs), this paper establishes a two-stage order allocation model considering demand updating and the FLSPs’ fairness preferences. This model is a multi-objective programming model, whose goal is to maximize profits of the LSI and the total utility of FLSPs. The ideal point method is used to obtain the optimal solution. In the numerical example, the impacts of FLSPs’ behavioral parameters and demand update parameters on the order allocation in the social services network are discussed. Besides, multi-methodological method is used to verify the theoretical perspectives through an empirical study of Tianjin SND Logistics Company. Our study obtains a few important conclusions. For example, when demand of the second stage is updated, there is an optimal updating time maximizing the supply chain performance. Increased demand of the second stage results in greater supply chain performance. When the demand during the second stage decreases, the bigger the difference of the fairness preference coefficients among FLSPs, the greater the LSI’s profits and the lower the FLSPs’ total utility will be. However, the difference of the fairness preference coefficients among FLSPs has little influence on the LSI’s profits and total utility of the FLSPs, when the demand during the second stage increases.

The influences of demand disruption on logistics service supply chain coordination: A comparison of three coordination modes

There are few studies on the influences of demand disruption on logistics service supply chain (LSSC) coordination in previous literature. Therefore, this paper will discuss an LSSC consisting of a logistics service integrator (LSI) and two functional logistics service providers (FLSPs) with demand disruption. LSI procures the same kind of logistics service capacity from these two FLSPs, sets a unified price and then sells to service market. The demand depends on retail price and service effort level. As different FLSPs may achieve different effort levels, which bring them different order quantities, there is competition on effort level between them. With all these conditions considered, three coordination modes (i.e. decentralized decision-making mode, supplier alliance decision-making mode and centralized decision-making mode) are established and compared. On this basis, demand disruption is taken into consideration and the corresponding decision changes are observed. Some interesting findings are obtained. For example, from the view of service effort level, supplier alliance decision-making mode makes FLSPs achieve lower effort level than decentralized decision-making mode does; from the view of decision robustness, when demand disruption occurs frequently, decisions made under supplier alliance decision-making mode changes less than those made under decentralized decision-making mode. At last, model application is deployed to verify the conclusions with a practical case of SND Logistics Company in China.

The optimal decision of customer order decoupling point for order insertion scheduling in logistics service supply chain

Customer demand for order insertions impacts the position of the customer order decoupling point (CODP) in a logistics service supply chain (LSSC). This paper focuses on how the parameters of inserted orders affect the position of the CODP when a logistics service integrator (LSI) is operating a mass customization logistics service. Considering customer demand for orders to be inserted, a CODP decision model for LSSCs is developed based on a two-echelon LSSC consisting of an LSI and several customers. The objectives of the model are to maximize the profit and to ensure the comprehensive satisfaction of the LSI. Conducting numerical analyses on a specific dataset, it was discovered that the scale effect coefficient and service volume of the inserted order have a clear influence on the CODP decision, while the order variation coefficient does not. Furthermore, the LSI will not accept an inserted order when the inserted order has a high variation coefficient or a low price.

Channel Coordination in Logistics Service Supply Chain considering Fairness

Logistics service supply chain (LSSC) is a new type of service supply chain. This paper investigates the channel coordination issue in a two-echelon LSSC composed of one logistics service integrator (LSI) and one functional logistics service provider (FLSP) under fairness concerns. The models for a reservation price-only contract under disadvantageous inequality and advantageous inequality are established, respectively, in which the procurement cost, the potential shortage cost, and the operation cost are considered under stochastic market demand. Based on this model, the LSI’s optimal reservation quantity can be determined. Furthermore, we analyze the impact of fairness concerns and the related costs on channel performance and channel coordination. The results are presented in four aspects:(1)channel coordination of the LSSC can be achieved under certain conditions when the LSI experiences advantageous inequality;(2)the spiteful behavior of the LSI leads to the reduction of the channel profit, and channel coordination cannot be achieved when the LSI suffers from disadvantageous inequality;(3)the LSI’s reservation quantity and the channel profit are affected by the LSI’s fairness concerns;(4)motivated by the concerns of fairness, the LSI’s reservation quantity is related not only to his procurement cost and shortage cost but also to the FLSP’s operation cost.

Capability Coordination in Automobile Logistics Service Supply Chain Based on Reliability

The paper builds a two-stage automobile Logistics Service Supply Chain (LSSC). The Logistics Service Integrator (LSI) is dominant. It integrates Functional Logistics Service Provider (FLSP). Considering the feature of non-storage and reliability, the buyback contract model was built under the stochastic demand. When the logistics capability that LSI wants to order is equivalent to FLSP willing to supply, the automobile LSSC reaches equilibrium. Compared with no contract, the buyback contract can coordinate the automobile LSSC better. Simulation results indicate that if the reliability increases, the optimal logistics capability order quantity, the buyback price and all expected profits decrease. If the penalty cost increases, the buyback price, the expected profits of LSI and LSSC decrease, while the optimal logistics capability order quantity and the expected profit of FLSP increase. Compared to the penalty cost, the relevant indexes are more sensitive to the reliability.

The two-stage batch ordering strategy of logistics service capacity with demand update

This paper discusses a logistics service integrator (LSI) orders logistics service capacity from a functional logistics service provider (FLSP) before the selling season with two opportunities. The optimal two-stage batch ordering strategy of LSI with demand update is studied. Standard batch size is introduced into LSI’s two-stage capacity ordering strategy model, which is built upon the decision-making sequence and actually observed demand signals between the two ordering instants. The model solution method is designed based on scenario analysis and enumerative algorithm. Sensitivity analysis of the optimal adjustment ordering time point is then carried out and a numerical analysis is presented.

Coordinating contracts for a three-lever logistics service supply chain

A three-lever logistics service supply chain (LSSC) consisting of a logistics service integrator (LSI), a logistics service provider (LSP), and a functional logistics service subcontractor (LSS) is discussed in this paper. Since the improvement of logistics service levels caused by the efforts of LSS can significantly affect the market demand for LSSC, a dynamic game theory model is developed to solve the coordinating contract design problem in this condition. A joint contract which combined with the option contract and the cost-sharing and revenue-sharing contract is designed. The option contract is between LSI and LSP, which are regarded as a whole to share revenue and cost with LSS in the two transactions of LSSC. The reasonable choice of parameters can attain the maximum of the expected profit of LSSC and the win-win good among all members. Finally, a corresponding numerical example is presented to illustrate the conclusions.

Capability Coordination in Agricultural Products Logistics Service Supply Chain with Revenue-sharing Contract

To solve the capability coordination in logistics service based on the agricultural products industry, a two-stage agricultural products Logistics Service Supply Chain (LSSC) was established with one agricultural products logistics service integrator and one functional logistics service provider. Based on the non-storage property of logistics service capability, the revenue-sharing contract model was built under the uncertain demand. The optimal logistics capability order quantity and the revenue-sharing coefficient were calculated when the agricultural products LSSC achieved coordination. Revenue-sharing contract can coordinate the agricultural products LSSC effectively compared with no contract. A numerical simulation was taken by MATLAB 7.0. The change of purchase price has no influence on the optimal logistics capability order quantity and the expected profit of agricultural products LSSC. It achieves a redistribution of members’ profits. With the increases of penalty cost, the optimal logistics capability order quantity and the expected profit of provider increase, while the expected profit of integrator and agricultural products LSSC decrease.

A scheduling model of logistics service supply chain based on the time windows of the FLSP’s operation and customer requirement

In the scheduling problem of logistics service supply chain (LSSC), the uncertainties of the functional logistics service provider’s (FLSP’s) operation time and customer requirement time will directly influence the logistics service integrator’s (LSI’s) time scheduling plan. In this paper, we explored the influences of time windows of the FLSP’s operation and customer requirement on the scheduling decision. A multi-objective programming model of the LSSC time scheduling is established, aiming to minimize total order operation cost of the LSSC, minimize the difference between the total expected operation time and customer requirement time, and maximize the satisfaction of functional logistics service providers. To simplify the model solution, this multi-objective model is changed into a single-objective model with ideal point method. In the following numerical analysis for a specific example, genetic algorithm is applied. The influences of some relevant parameters on the scheduling performance are discussed. Firstly, with the increases of FLSPs’ operation time range and the postponement proportionality coefficient of customer requirement time, the optimal scheduling performance of LSSC will increase and then tend to be stable. Secondly, the customer requirement time could not be compressed too much and have a minimum in order to obtain a feasible solution. Thirdly, the time windows of the FLSP’s operation and customer requirement have significant interactions. The time window of customer requirement will expand with the increase of the time window of the FLSP’s operation.

A multi-period order allocation model of two-echelon logistics service supply chain based on inequity aversion theory

By considering a two–echelon supply chain composed of a logistics service integrator (LSI) and several functional logistics service providers (FLSPs), this paper builds an adjusted order allocation utility (AOAU) function of FLSP during multi–period based on inequity aversion theory, and then establishes an order allocation model within multi–period logistics service supply chain. When FLSP's inequity feeling exceeds its patience limit, LSI can make quick or postpone improvement about the allocation plan for the next period. The aim of this proposed model includes two goals: one is to maximise the profit of LSI and the other is to maximise the comprehensive order allocation utility (COAU) of FLSPs. The ideal point method is used to obtain the optimal solution and a numerical example is given by software MATLAB 7.10. The effects of FLSPs' behaviour parameters on order allocation are analysed in detail. The results show that the profit of LSI and the COAU of FLSPs will decrease with the increase of inequality aversion coefficients of FLSPs but it cannot be increased endlessly through changing the patience limit of FLSPs. Additionally, postponed improvement adopted to order allocation model has better effects than that of prompt improvement.

Revenue-Sharing Contract Models for Logistics Service Supply Chains with Mass Customization Service

The revenue-sharing contract is one of the most important supply chain coordination contracts; it has been applied in various supply chains. However, studies related to service supply chains with mass customization (MC) are lacking. Considering the equity of benefit distribution between the members of service supply chains, in this paper, we designed two revenue-sharing contracts. The first contract for the maximum equity of a single logistics service integrator (LSI) and single functional logistics service provider (FLSP) in a two-echelon logistics service supply chain was designed by introducing the fair entropy function (“one to one” model). Furthermore, the method is extended to a more complex supply chain, which consists of a single LSI and multiple FLSPs. A new contract was designed not only for considering the equity of an LSI and each FLSP but also for the equity between each FLSP (“one toN” model). The “one to one” model in three-echelon LSSC is also provided. The result exemplifies that, whether in the “one to one” model or “one toN” model, there exists a best interval of customized level when the revenue-sharing coefficient reaches its maximum.