Research on Measurement and Application of China’s Regional Logistics Development Level under Low Carbon Environment

To solve the problem of fuzziness and randomness in regional logistics decarbonization evaluation and accurately assess regional logistics decarbonization development, an evaluation model of regional logistics decarbonization development is established. First, the evaluation index of regional logistics decarbonization development is constructed from three dimensions: low-carbon logistics environment support, low-carbon logistics strength and low-carbon logistics potential. Second, the evaluation indexes are used as cloud model variables, and the cloud numerical characteristic values and cloud affiliation degrees are determined according to the cloud model theory. The entropy weight method is used to determine the index weights, and the comprehensive determination degree of the research object affiliated to the logistics decarbonization level is calculated comprehensively. Finally, Beijing-Tianjin-Hebei region is used as an example for empirical evidence, analyzing the development logistics decarbonization and its and temporal variability in Beijing, Tianjin and Hebei provinces and cities. The results of the study show that the development logistics decarbonization in Beijing, Tianjin and Hebei Province has been improved to different degrees during 2013–2019, but the development is uneven. Developing to 2019, the three provinces and cities of Beijing, Tianjin and Hebei still have significant differences in terms of economic environment, logistics industry scale, logistics industry inputs and outputs, and technical support.

Prediction of Regional Logistics Heat and Coupling Development between Regional Logistics and Economic Systems

The research on logistics heat facilitates the understanding of the drivers of regional logistics development. However, many scholars ignore the difference between prediction methods in terms of attributes and focal points of data analysis during the selection of regional logistics heat prediction model. Regional logistics interacts with regional economy. However, the studies on the coupling development between the two systems fail to make a detailed analysis in the light of their actual situation. Therefore, the evaluation of the coordination degree is often biased. To solve the problem, this paper probes into the prediction of regional logistics heat and the coupling development between regional logistics and economic systems. Firstly, an index system was established to measure the level of coupling development between the two systems, and a grey relational analysis was performed on the indices, leading to the evaluation results on coordination degree. Next, a composite model of GM (1, 1) and backpropagation (BP) neural network was proposed, and the deviation interval of the composite predictions was predicted based on Markov chain prediction model. The proposed algorithm proved effective through experiments.

Assessment of the logistics potential of the region (on the example of the Vitebsk region)

The article is devoted to the problem of studying the logistics potential of the region. Theoretical studies of the concept of "logistics potential" are presented. The review of the main methods of assessing the regional logistics potential is carried out, the main groups of factors are identified, on the basis of which the author's methodology for assessing the logistics potential of the region is proposed. The "bottlenecks" and "points" of the growth of the logistics potential of the Vitebsk region are identified and practical recommendations for their use are given.

Algorithm for Solving Problem of Designing Regional Logistics Infrastructure

The paper considers an algorithm for solving the problem of finding the optimal location of key objects of transport and warehouse infrastructures within the framework of a methodological approach to designing logistics infrastructure in the territory of the region of the countries. The methodological approach includes three stages. At the first stage, areas are determined where it is advisable to locate key objects of the regional logistics infrastructure. Further, using the models developed by the authors, the linking of warehouse infrastructure objects on the ground has been carried out and, taking into account the designed warehouse network, the optimal dislocation of transport infrastructure objects has been determined. To find the optimal locations for the objects for regional logistics infrastructure facilities, the authors propose an algorithm that is applicable both for building warehouse and transport infrastructures due to the similarity of the models. The algorithm is based on the method of constructing a sequence of plans. At the initial stage, the final expansion is constructed for the set of plans under consideration. For a given set, a minorant has been determined for the cost function associated with the placement and maintenance of infrastructure facilities, the movement of goods, and the haul of an empty vehicle. After that, an iterative algorithm has been formed that determines the sequence of optima of the minorant on a sequence of nested sets. At the first step, an element of the set of plans has been found that minimizes the minorant, at the next step, the found element is excluded from the set under consideration, and a new optimum is sought on the remaining set for which the minorant takes the minimum value. To eliminate multiple plans, it is advisable to use dynamic programming procedures. The limits of applicability of the method for constructing a sequence of plans are determined by the ability to construct an extension of the set of plans for placing objects, select a minorant on it, and build an algorithm for ordering optima.

SPATIAL CONNECTION CHARACTERISTICS AND DRIVING MECHANISM OF REGIONAL LOGISTICS IN GUANGDONG-HONG KONG-MACAO GREATER BAY AREA

The paper adopted the entropy weight TOPSIS method and the gravity model to explore the characteristics of logistics spatial connection of Guangdong-Hong Kong-Macao Greater Bay Area that includes nine prefecture-level cities and two special administrative regions, and analyzed the driving factors of the formation of logistics spatial connection pattern by geographical detector model. The results shows that: There are obvious imbalance in the comprehensive capacity of logistics in different regions, and the cities around the Pearl River estuary are generally strong in the logistics quality, like Guangzhou, Shenzhen and Hong Kong. The total amount of logistics links in different cities is significantly various. The logistics connection between cities are mainly weak, and the strong links are concentrated between Hong Kong and Shenzhen. In addition, Hong Kong, Guangzhou and Shenzhen are the three core nodes of the regional logistics network in Guangdong-Hong Kong-Macao Greater Bay Area. Industrial structure, economic scale, population scale, consumption level, the development of post and telecommunications industry are the main factors for the formation of the logistics spatial connection pattern. Moreover, these factors have a prominent driving effect on the cities with large amount of logistics links.

Managing regional logistics in times of crisis: a COVID-19 case study

PurposeCoronavirus Disease 2019 (COVID-19) is a pandemic with unique regional logistics management (RLM) challenges to respond to the chaos created by the crisis and to restore normality for operations and supply chains in home nations. The purpose of this article is to explore RLM in times of crisis from the perspective of public authorities responsible for combating the COVID-19 pandemic. The article also discusses the significance of crisis-driven RLM for humanitarian logistics and supply chain (HLSC) management.Design/methodology/approachGrounded on an inductive case study logic and guided by a constructivist perspective, this research involves semi-structured interviews with 15 managers and strategists responsible for the RLM of COVID-19 to capture lessons learnt so far from mitigating the transmission and spread of COVID-19. Underpinning the research is a conceptual RLM model premised on coordination, communication, and containment mechanisms (the 3Cs of crisis-driven logistics), as crisis response.FindingsThe study finds that the triggering of regional logistics in times of crisis for the COVID-19 case involves taskforce teams with centralisation for crisis readiness, information infrastructure with digitalisation for crisis protocols, and capacity calculations with orchestration for crisis scenarios. The study also finds that navigating the challenges for the 3Cs of crisis-driven logistics entails forward-thinking leadership for culture-based commitments, first-hand clarity for compliance-based campaigns, and far-reaching solidarity for compassion-based contributions.Originality/valueThis article addresses the gap in knowledge on RLM and potential priorities that underpin crisis-driven RLM strategies for HLSCs. The research is original in its argument for regional perspectives on logistics strategies that contribute to the “viability” and “integrity” of HLSCs. The research also uniquely focuses on RLM in times of crisis and proposes a conceptual RLM model of strategies for enhancing HLSCs.

BUILDING AN INTELLIGENT TRANSPORT SYSTEM ON THE CRIMEAN PENINSULA AS A METHOD TO INCREASE THE EXCHANGE RATE OF REGIONAL LOGISTICS PROCESSES

The well-known approaches to the process of building an intelligent transport sys tem are considered. The problems of digitalization of the economy are posed. The theory of economic zoning is proposed as a basis for the design of an intelligent transport system on the Crimean penin sula. To solve the problem, the methods of collecting information, analyzing documentation, generaliz ing, grouping, Voronoi diagram were used.