From Logistics to Collaborative Logistics — A Theoretical Approach

Optimal quoting of delivery time by a third party logistics provider: The impact of shipment consolidation and temporal pricing schemes

PurposeThe purpose of this study is to analyse the extent of the integration between manufacturers and third party logistics (TPL) providers at present and how the integration is expected to develop in the near future. The focus is on studying what tasks are part of the cooperation, what information and communications technology (ICT) tools are used for support, and what types of services are supplied and are expected to be supplied by TPL providers in the future.Design/methodology/approachA multiple case study of seven manufacturers and TPL providers is conducted. As the basis for the study a literature review is presented focusing on supply chain management and TPL provider integration as well as operationalisation of the integration concept. A framework is chosen for developing a detailed interview guide.FindingsCooperation is primarily found in sub‐processes of three out of the eight business processes studied. Further integration in the same processes is expected, based on ICT tools and with a focus on cost. ICT competences are primarily seen as a qualifier not a differentiator. Because the future TPL industry is expected to be characterised by more standardised services, more segmented markets for the various services and more intense competition, the manufacturers do not expect increased dependence on the TPL providers.Research limitations/implicationsManagerial and behavioural components are not part of this study and their effect on integration will require further investigation.Originality/valueFrom a supply chain management perspective, the study sheds light on a rarely explored area concerning the integration between manufacturers and TPL providers and its future development.

Collaborative logistics is a kind of supply chain management, involving cooperation between companies to meet customer needs. This is a complex process that requires coordination among all parties. It can be divided into three main stages: planning, implementation and monitoring. The purpose of this study is to determine the best mode of resource selection in collaborative logistics using genetic algorithms. The first stage of collaborative logistics is planning, including determining customer needs, defining inventory levels, and determining transportation routes. This is a complex process because it involves many different types of resources and products. In this paper, we will discuss how to use genetic algorithms to improve collaborative logistics. When improving the collaborative logistics process, the first thing to consider is to determine all necessary resources and products required for such supply chain management. This will help eliminate unnecessary costs, because only those items that are really needed will be purchased from suppliers. This paper analyzes the framework of collaborative logistics mechanism, uses analytic hierarchy process (AHP) to preliminarily screen logistics resources to obtain the candidate resource pool required by the collaborative system, and proposes an effective resource selection process using the improved contract network protocol method based on the collaborative logistics network model. The negotiation process determines the basic rates for transportation, warehousing, and other items in the collaborative logistics system, and achieves the aggregation and collaboration of logistics tasks through solving the collaborative logistics network model. Finally, the fuzzy comprehensive evaluation method is used to calculate the allocation proportion of additional profits in the collaborative system.

Collaboration is perceived as a powerful tool for companies to deal with an increasingly demanding global economic environment. Collaboration impact upon the logistics processes is analyzed in this chapter. Logistics naturally implies the concurrency of a set of companies being part of products and services value chain. However, collaborative logistics imposes new challenges that effectively faced by companies and government institutions will produce the expected return. Such challenges relate to effective decision making process involving logistics activities planning, scheduling, control, and coordination at different companies being part of the logistics network. These decision making processes require the effective capability to capture, process, and analyze information on processes, partners, environment, regulations, etc. That information is, of course, dynamic, and it is available in a scattered way all through a variety of sources, periodicity, and formats. Effective and efficient tools for capturing, classifying, processing, and report useful information for supporting the collaborative logistics decision making processes are required. Large amounts of digital text available on the web contain useful information for enabling collaborative logistics. The amount of digital text it is expected to increase significantly in the near future, making the development of data analysis applications an urgent need. Information gathering has been traditionally faced integrating systems and databases at the various institutions and companies participating in the logistics network. This approach has at least two difficulties that have not been solved properly: 1) It requires the data be available in structured databases and stored in terms of the same attributes, and 2) Organizations need to provide access to their systems for obtaining and processing the data. An alternative approach is using data available in the web as input to automatic text classifiers implemented with machine learning techniques. Automatic text classification (or categorization) is defined as the assignment of a Boolean value to each pair (dj,ci) belonging to the set D×C, where D is the domain of documents and C = {c1,...c|C|} is the set of predefined labels. Binary classification is the most simple and widely studied case, in which a document is classified into one of two mutually exclusive categories or classes. Document representation has a high impact on the task of classification. Some elements used for representing documents are: N-grams, single-word, phrases, or logical terms and statements. The vector space model is one of the most widely used models for ad-hoc information retrieval, mainly because of its conceptual simplicity and the appeal of the

We recently observe that some giant e‐tailers (e.g., Amazon and JD.com) introduce marketplace channels by allowing third‐party sellers to sell products through their platforms. Logistics service acts as a vital role in the operation of online platforms. In practice, the platform can outsource logistics service to third‐party logistics providers (named as a third‐party logistics strategy) or establish a self‐run logistics network to distribute products (named as a self‐run logistics strategy). This paper investigates the e‐tailer's logistics service strategy in the presence of the marketplace channel's introduction. We reveal that the cost of logistics service plays a major role in determining the optimal logistics strategy. The self‐run logistics strategy provides a low logistics service cost to the platform, which results in a higher consumer surplus in comparison with the third‐party logistics strategy. Further, we find that when the logistics service cost is low, the platform prefers to establish self‐run logistics in the presence of the marketplace channel. Finally, our results show that under the third‐party logistics strategy, the platform benefits from the marketplace channel in the presence of an intermediate commission fee and a low discount factor. Based on game‐theoretic models, some managerial insights are suggested for online retailers to choose the optimal logistics service strategy in the presence of introducing the marketplace channel.

Designing logistics systems means dealing with complex planning and decision problems. The following chapter will examine details and strategies in logistics planning with a focus on planning logistics networks, warehouse networks, and transport networks.

For most of the manufacturing firms, logistics is not considered to be a core competency and it is often performed by Third Party Logistics Provider (TPLP). The present work describes an efficient decision framework for TPLP evaluation and selection in supply chain. The objective of this paper is to explain how an Analytic Hierarchy Process (AHP) and Performance Value Analysis (PVA) algorithm can be used to capture and analyse Significant Categories (SCs) and Performance Indicators (PIs) for ranking the TPLPs effectively. The application of decision framework for TPLP evaluation and selection has been demonstrated with a case situation.

Supply chain fulfills its customer's demand by a network of companies, mainly consisting of suppliers, manufacturers and third party logistics providers (thereafter 3PLs). Firstly, the related literatures are reviewed. And based on Venn diagram, the information sharing mechanism is analyzed to indicate the relationship between the different shared information. Moreover, three information-sharing models are proposed and analyzed, which are the point-to-point model, the interface model, and the integrated manage model. Integrated with the aforementioned analysis, the view is provided to select the matching information sharing model under different conditions. The paper ends with a discussion of directions for future research.

The article considers the strategic guidelines of the logistics activities of poultry enterprises. It is noted that the strategies of minimizing logistics costs and investing in the logistics network, maximizing and improving logistics services, maximizing income and profits, increasing the competitive advantages of the enterprise, logistics outsourcing are the most widely used logistics strategies. It is proved that the purpose of creating a logistics system is to harmonize the interests of producers, suppliers and consumers. It is established that an important factor in improving the strategic activities of the enterprise is the introduction of the principles of distribution logistics. This concept involves the use of a systematic approach and integrated planning, as well as management of the entire flow of feed, materials, breeding and commercial poultry products in various areas from suppliers, through manufacturers of breeding and breeding products, distribution centers, to the final individual and corporate consumers of poultry products. The main stages of the business process of integration of a poultry enterprise in the supply chain are schematically shown. The necessity of introduction of new, more progressive forms of service in the process of goods movement can be achieved. The need to use regional distribution centers of poultry enterprises in the supply chain, which will significantly reduce the cost of delivery of their products through the formation of optimal transport batches of products from different manufacturers, its packaging and labeling.

The purpose of this study is to demonstrate the potential use of quality function deployment (QFD) in the selection of cross-border Third Party Logistics (3PL) provider. Our approach involves extending conventional QFD with Bayesian Networks (BN) with ranked nodes and a multi-criteria decision analysis method such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This way, cross-border 3PL provider selection process will incorporate voice of overseas customers and expert knowledge. Cooperating with Lovely Wholesale, a cross-border e-commerce wholesaler of women's clothing; we record the voice of customer (VOC) through a survey, develop decision criteria and compute their relative importance weights and build a correlation matrix using the House of Quality (HOQ). A causal nexus graph is formed based on the correlation analysis. We use a parameterization of BN called Ranked Nodes, which lets experts contribute their expertise in the form of natural language phrases. BN produces the decision matrix while the relative importance weights are used as weights of criteria in ranking with TOPSIS. A successful ranked list of alternatives confirms that the methodology developed in this work may aid in selecting the most appropriate cross-border 3PL provider considering the voice of customer.

Growing service science concerns have motivated businesses to carefully apply outsourcing logistics achieving core competition. Third party logistics plays an important role in achieving outsourcing logistics by providing customers with the opportunity to outsource logistics to the third party logistics providers. An efficient third party logistics contract may lead to a significant return on outsourcing as well as a significantly increased competitiveness in the market. In order to ensure efficiency, the selection of parameters in the third-party outsourcing contract is a crucial step in initializing logistics related practices. This study aims to efficiently assist the decision makers in determining the optimization parameters of third-party contract using an economic model based on gaming theory. A numerical example is also included in the study to demonstrate the steps of the proposed model. In the end, the procedure of decision-making in optimizing the contract is concluded.

Agricultural supply chain is in general open and dynamic attributed and negotiation is a key strategy to realize collaboration among different entities involved. However, traditional static and offline negotiation strategy may not function well, an agricultural supply chain centered on third party logistics will provide a new collaborative relationship among agricultural materials suppliers, agricultural cooperatives, farmers, agricultural products demanders and third party logistics providers. This paper proposes a novel adaptive negotiation strategy for agricultural supply chain centered on third party logistics. The negotiation strategy consists of an evaluation function in terms of integrity and risk preferences, a concession function in terms of concession preference, time and resources, and a generation function in terms of opponent’s behaviors. Afterwards, an procedure was proposed to solve the negotiation strategy. Finally, a simulation experiment was employed to verify the effectiveness of the negotiation strategy.

Fierce global competitiveness and heightened expectations of customers are forcing companies to forge collaborative partnerships with Third Party Logistics (3PL) service providers. Most companies cite greater flexibility, operational efficiency, improved customer service levels, enhanced supply chain performance and better focus on their core businesses as part of the advantages of engaging the services of third party logistics providers. Despite the endless advantages of third party logistics and supply chain activities, a lot of relationships either fail or are dissolved. The paper attempts to analyse the management of 3PL relationship and the impact on overall satisfaction of user organisations with the expected business performance and productivity of relationships. Research findings indicate that high-involvements in 3PL relationships, leading to collaborative partnerships, will have a positive impact on increased usage of 3PL services.

Supply chain risk management processes are among the most important activities in the value chain of any industry. The supply chain risk management process includes different activities, focused on the identification, measurement, assessment, and mitigation of the main risk sources that can affect a supply chain. The increasing complexity facing global supply chains generates the need for suppliers to collaborate in different processes in a supply chain. In this context, Third Party Logistics Providers (3PL) have been widely promoted by the phenomenon of outsourcing, on which companies increasingly rely. The growth in logistics outsourcing is mainly attributed to the benefits it brings in terms of reducing costs, improving performance, allowing companies to focus on their core businesses and building virtual enterprises through strategic alliances. In this chapter we develop a model to identify the operational risk factors of a 3PL provider.

Third party logistics (3PL) service providers play a growing responsibility in the management of supply chain. The global and competitive business environment of 3PLs has recognized the significance of a speedy and proficient service towards the customers in the past few decades. Particularly in warehousing, distribution, and transportation services, a number of customers anticipate 3PLs to improve lead times, fill rates, inventory levels, etc. Therefore, the 3PLs are under demands to convene a range of service necessities of customers in an active and uncertain business environment. As a consequence of the dynamic environment in which supply chain must operate, 3PLs should sustain an effective distribution system of high performance and must make a sequence of inter-related decisions over time for their distribution networks. Warehouses play an important role in sustaining the continual flow of goods and materials between the manufacturer and customers. The performance of the 3PL supply chain network can be effortlessly enhanced by a balanced allocation of customers to warehouses. In this paper, the authors develop a genetic algorithm and a particle-swarm-optimisation algorithm for solving the balanced allocation problem and the results are encouraging.