Problems of Decision-Making in Implementation of Technological Innovations in Transport Industry

The article considers the features of transport as an object of technological innovation, due, on the one hand, to the service nature of the main activity and the specifics of innovative processes during provision of transport and logistics services, and, on the other hand, to the high capital intensity and technological complexity of the infrastructure transport complex, which is the focus point of technological innovation.The objective of the article is to substantiate the initial prerequisites for developing an alternative approach to making strategic decisions on development of transport organisations based on technological innovations, which, besides the traditional justification of economic efficiency, considers several non-economic factors. The method of substantiation is a systemic strategic analysis, which allows to study the features of the transport complex in the context of the factors of external environment and their dynamics.Regarding the Russian Federation, the scale of the national territory, natural and climatic diversity and uneven territorial distribution of the resource and production base determine the special role and place of transport in the national economy, which quite often leads to the need to make decisions on development of the transport complex based on predominantly non-economic factors (such as security, reliability, environmental friendliness, etc.) and on scientific, technical, political and socio-economic forecasts. At the same time, private enterprises (with or without participation of the state) dominate currently almost all transport sectors where they operate on the principles of profitability, investment attractiveness and competitiveness, which leads to inconsistency of internal decision-making criteria in the field of technological strategies.The ongoing change in the technological paradigm is an additional and significant factor determining trends in transport developments. It is based on the processes of digitalisation and digital transformation of the transport and logistics business. The problems of decision-making in implementation of technological innovations in transport industry, arising from its peculiarities, necessitate a revision of approaches since economic assessments of efficiency are not always able to reflect the real needs and feasibility of choosing mainstream trends in technological development of the transport system.The analysis of the features of the transport and logistics industry based on universal experience and cases in Russian practices in the context of formation of a new technological paradigm makes it possible to substantiate the methodology for making strategic decisions on implementation of technological innovations.

Using AI and ML to predict shipment times of therapeutics, diagnostics and vaccines in e-pharmacy supply chains during COVID-19 pandemic

PurposeThis paper aims to address the pressing problem of prediction concerning shipment times of therapeutics, diagnostics and vaccines during the ongoing COVID-19 pandemic using a novel artificial intelligence (AI) and machine learning (ML) approach.Design/methodology/approachThe present study used organic real-world therapeutic supplies data of over 3 million shipments collected during the COVID-19 pandemic through a large real-world e-pharmacy. The researchers built various ML multiclass classification models, namely, random forest (RF), extra trees (XRT), decision tree (DT), multilayer perceptron (MLP), XGBoost (XGB), CatBoost (CB), linear stochastic gradient descent (SGD) and the linear Naïve Bayes (NB) and trained them on striped datasets of (source, destination, shipper) triplets. The study stacked the base models and built stacked meta-models. Subsequently, the researchers built a model zoo with a combination of the base models and stacked meta-models trained on these striped datasets. The study used 10-fold cross-validation (CV) for performance evaluation.FindingsThe findings reveal that the turn-around-time provided by therapeutic supply logistics providers is only 62.91% accurate when compared to reality. In contrast, the solution provided in this study is up to 93.5% accurate compared to reality, resulting in up to 48.62% improvement, with a clear trend of more historic data and better performance growing each week.Research limitations/implicationsThe implication of the study has shown the efficacy of ML model zoo with a combination of base models and stacked meta-models trained on striped datasets of (source, destination and shipper) triplets for predicting the shipment times of therapeutics, diagnostics and vaccines in the e-pharmacy supply chain.Originality/valueThe novelty of the study is on the real-world e-pharmacy supply chain under post-COVID-19 lockdown conditions and has come up with a novel ML ensemble stacking based model zoo to make predictions on the shipment times of therapeutics. Through this work, it is assumed that there will be greater adoption of AI and ML techniques in shipment time prediction of therapeutics in the logistics industry in the pandemic situations.

Evaluation of Green Logistics Efficiency in Jiangxi Province Based on Three-Stage DEA from the Perspective of High-Quality Development

The high-quality development of the logistics industry plays an important role in high-quality economic development. Green logistics is attracting more attention, owing to environmental concern. Based on the five concepts of “innovation, coordination, green, openness and sharing” of high-quality economic development, the input–output indicators of green logistics efficiency (GLE) have been designed. The correlation between the green logistics input and output indicators have been analyzed by Pearson, and the green logistics efficiency of 11 cities in Jiangxi Province has been calculated by three-stage DEA. The evolutionary characteristics of the high-quality development of green logistics efficiency in Jiangxi Province were analyzed and evaluated. The conclusions were achieved as follows: (1) Nanchang, Xinyu and Ganzhou city are at the forefront of efficiency, and are less affected by environmental factors. The logistics efficiency of other cities is obviously affected by environmental factors. (2) The comprehensive technical efficiency (TE) of green logistics in Jiangxi Province is strongly influenced by scale efficiency (SE). The poor scale efficiency reduces the comprehensive technical efficiency of green logistics. (3) There is a positive correlation between high-quality economic development and logistics efficiency. In these cities of Jiangxi province (Nanchang, Ganzhou, Jiujiang, etc.) the share of total economy and green logistics efficiency is high. This study proves that Jiangxi province is moving towards high-quality economic development due to good environmental protection. (4) In 2017, Jiangxi Province was recognized as one of the national ecological civilization pilot region by the State Council. Green logistics efficiency in Jiangxi Province showed an inflection point in 2017, indicating that the green concept is becoming more and more popular. From the government to enterprises, the province has achieved initial results in promoting the transformation of the economic development mode. It aims to provide reference for the high-quality development of other provinces.

Emergency Response, Influence and Lessons in the 2021 Compound Disaster in Henan Province of China

Henan province, located in central China, suffered a heavy rainstorm and an outbreak of COVID-19 from the middle of July to the middle of August. We review and investigate the emergency response to these two events. The influence of the compound disaster on provincial economic operations, fixed assets, consumer goods, the logistics industry, high-tech manufacturing, and strategic emerging industries is analyzed in detail. Since the province’s economic situation has been positive for a long time, the influence of the compound disaster was short-term. The countermeasures to the pandemic were efficient since they had previously been in practice at various times in 2020. However, in the face of unusual disasters such as the rainstorm, the gap between early warning and emergency response needs to be bridged, and the sources of relief funds should be diversified.

An Integrated Impact of Blockchain Technology on Suppy Chain Management and the Logistics Industry

The benefits of blockchain technology for supply chain management and logistics have been authenticated in recent years. It can support transparency and guarantee eventual, system-wide consensus on the validity of an entire history of transactions. As Conte de Leon et al. defined, blockchains would cause disrupting transformations in all types of industries when used in supply chain management. Logistic companies should engage in blockchain technology to adapt rapidly to changing market conditions and needs in today's dynamic business environment. Thus, this chapter provides a comprehensive overview of blockchain technology and focuses on crucial supply chain capabilities to create such transparency, flexibility, and mutual trust between supply chain partners.

A study of strategic group mapping and understanding mobility barriers in Indian logistic industry

The purpose of this research was to identify the strategic groups present in the Indian logistics industry and discuss the mobility barriers across the strategic groups. Secondary research was performed by collecting data from online sources and results were vetted by experts in supply chain management through convergent interviews. The research identified nine strategic groups in Indian logistic industry. Requirement of group specific fleet structures, assets, expertise in Value-added services were some prominent intergroup mobility barriers identified. Managers could devise ‘End to End’ supply chain solutions by collaborating with firms of other strategic groups as identified in the study.

The Impact of Logistics on Marketing Margin in the Philippine Agricultural Sector

The logistics industry is a fundamental aspect of fulfilling the supply chain in agriculture. Agricultural farmers in the Philippines often use the services of middlemen to transact on their behalf since these intermediaries possess better information, and engaging in logistics affects the marketing margin in the process. Frequently, logistics costs cause marketing margin to increase, leading to high farm-retail prices of agricultural goods. This paper examines if the existence of middlemen improves farmers' wages even with the additional logistics costs incurred. The variables' secondary data were all gathered from the Philippine Statistics Authority, and its annual frequency spanned the period of 1995 to 2019. Using Ordinary Least Squares (OLS) regression analysis procedure and diagnostic tests prove that logistics cost negatively affects marketing margin while farmers' wages have a positive relationship. The findings of this study address the presence of a longer supply chain, asymmetric information, technology, storage and facilities, and added logistics costs in agricultural transactions. Although middlemen have greater market power than the farmers, these mediators are still affected by the changes in the logistics costs since it is unavoidable for them to reduce the price due to the need to competitively sell the commodities.

Contract design for the fourth party logistics considering tardiness risk

Nowadays, tardiness has become a significant risk in the logistics industry. To address this problem, we introduce the tardiness risk index to quantify both the magnitude of the tardiness risk and the maximum probability of tardiness occurring. In this paper, we investigate the contract design problem with the tardiness risk index to mitigate the tardiness risk when a fourth-party logistics company (4PL) delegates the delivery task of a client to a third-party logistics company (3PL). Specifically, the contracts are designed in a decentralized system with information symmetry and information asymmetry when 3PL is risk neutral and risk averse. Furthermore, the incentive problems demonstrated that the 3PL is encouraged to make the optimal effort for delivery and the 4PL determines the optimal fixed payment and penalty coefficient. Through analyzing the experimental simulation results, we can find that the contract can effectively mitigate the tardiness risk and the maximum probability of risk occurrence.